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Wolken M, Sun T, McCall C, Schneider R, Caton K, Hundley C, Hopkins L, Ensor K, Domakonda K, Kalvapalle P, Persse D, Williams S, Stadler LB. Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections. WATER RESEARCH 2023; 231:119648. [PMID: 36702023 PMCID: PMC9858235 DOI: 10.1016/j.watres.2023.119648] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 12/16/2022] [Accepted: 01/18/2023] [Indexed: 06/17/2023]
Abstract
Wastewater surveillance is a passive and efficient way to monitor the spread of infectious diseases in large populations and high transmission areas such as preK-12 schools. Infections caused by respiratory viruses in school-aged children are likely underreported, particularly because many children may be asymptomatic or mildly symptomatic. Wastewater monitoring of SARS-CoV-2 has been studied extensively and primarily by sampling at centralized wastewater treatment plants, and there are limited studies on SARS-CoV-2 in preK-12 school wastewater. Similarly, wastewater detections of influenza have only been reported in wastewater treatment plant and university manhole samples. Here, we present the results of a 17-month wastewater monitoring program for SARS-CoV-2 (n = 2176 samples) and influenza A and B (n = 1217 samples) in 51 preK-12 schools. We show that school wastewater concentrations of SARS-CoV-2 RNA were strongly associated with COVID-19 cases in schools and community positivity rates, and that influenza detections in school wastewater were significantly associated with citywide influenza diagnosis rates. Results were communicated back to schools and local communities to enable mitigation strategies to stop the spread, and direct resources such as testing and vaccination clinics. This study demonstrates that school wastewater surveillance is reflective of local infections at several population levels and plays a crucial role in the detection and mitigation of outbreaks.
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Affiliation(s)
- Madeline Wolken
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA; Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center, 1200 Pressler Street, Houston, TX, USA
| | - Thomas Sun
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA
| | | | - Kelsey Caton
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Courtney Hundley
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Loren Hopkins
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA; Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Katherine Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, USA
| | - Kaavya Domakonda
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | | | - David Persse
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA; Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, USA; City of Houston Emergency Medical Services, Houston, TX, USA
| | - Stephen Williams
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, USA
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, USA.
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52
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Henriques TB, Cassini ST, de Pinho Keller R. Contribution of wastewater-based epidemiology to SARS-CoV-2 screening in Brazil and the United States. JOURNAL OF WATER AND HEALTH 2023; 21:343-353. [PMID: 37338314 PMCID: wh_2023_260 DOI: 10.2166/wh.2023.260] [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-based epidemiology (WBE) is a valuable tool for investigating the existence, prevalence, and spread of pathogens, such as SARS-CoV-2, in a given population. WBE, proposed as part of the SARS-CoV-2 surveillance strategy for monitoring virus circulation, may complement clinical data and contribute to reducing the spread of the disease through early detection. In developing countries such as Brazil, where clinical data are scarce, information obtained from wastewater monitoring can be crucial for designing public health interventions. In the United States, the country with the largest number of confirmed SARS-CoV-2 cases worldwide, WBE programs have begun to be carried out to investigate correlations with coronavirus disease 2019 (COVID-19) clinical data and support health agencies in decision-making to prevent the spread of the disease. This systematic review aimed to assess the contribution of WBE to SARS-CoV-2 screening in Brazil and the United States and compare studies conducted in a developed and developing country. Studies in Brazil and the United States showed WBE to be an important epidemiological surveillance strategy in the context of the COVID-19 pandemic. WBE approaches are useful for early detection of COVID-19 outbreaks, estimation of clinical cases, and assessment of the effectiveness of vaccination program.
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Affiliation(s)
- Taciane Barbosa Henriques
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
| | - Servio Túlio Cassini
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
| | - Regina de Pinho Keller
- Sanitation Laboratory, Department of Environmental Engineering, Federal University of Espírito Santo, Vitória, Espirito Santo, Brazil E-mail:
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53
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Ash KT, Li Y, Alamilla I, Joyner DC, Williams DE, McKay PJ, Green BM, Iler C, DeBlander SE, North CM, Kara-Murdoch F, Swift CM, Hazen TC. SARS-CoV-2 raw wastewater surveillance from student residences on an urban university campus. Front Microbiol 2023; 14:1101205. [PMID: 36846780 PMCID: PMC9948028 DOI: 10.3389/fmicb.2023.1101205] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
The COVID-19 pandemic brought about an urgent need to monitor the community prevalence of infection and detect the presence of SARS-CoV-2. Testing individual people is the most reliable method to measure the spread of the virus in any given community, but it is also the most expensive and time-consuming. Wastewater-based epidemiology (WBE) has been used since the 1960s when scientists implemented monitoring to measure the effectiveness of the Polio vaccine. Since then, WBE has been used to monitor populations for various pathogens, drugs, and pollutants. In August 2020, the University of Tennessee-Knoxville implemented a SARS-CoV-2 surveillance program that began with raw wastewater surveillance of the student residence buildings on campus, the results of which were shared with another lab group on campus that oversaw the pooled saliva testing of students. Sample collection began at 8 am, and the final RT-qPCR results were obtained by midnight. The previous day's results were presented to the campus administrators and the Student Health Center at 8 am the following morning. The buildings surveyed included all campus dormitories, fraternities, and sororities, 46 buildings in all representing an on-campus community of over 8,000 students. The WBE surveillance relied upon early morning "grab" samples and 24-h composite sampling. Because we only had three Hach AS950 Portable Peristaltic Sampler units, we reserved 24-h composite sampling for the dormitories with the highest population of students. Samples were pasteurized, and heavy sediment was centrifuged and filtered out, followed by a virus concentration step before RNA extraction. Each sample was tested by RT-qPCR for the presence of SARS-CoV-2, using the CDC primers for N Capsid targets N1 and N3. The subsequent pooled saliva tests from sections of each building allowed lower costs and minimized the total number of individual verification tests that needed to be analyzed by the Student Health Center. Our WBE results matched the trend of the on-campus cases reported by the student health center. The highest concentration of genomic copies detected in one sample was 5.06 × 107 copies/L. Raw wastewater-based epidemiology is an efficient, economical, fast, and non-invasive method to monitor a large community for a single pathogen or multiple pathogen targets.
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Affiliation(s)
- K. T. Ash
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - Y. Li
- Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, TN, United States
| | - I. Alamilla
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - D. C. Joyner
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - D. E. Williams
- Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - P. J. McKay
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - B. M. Green
- Department of Microbiology, University of Tennessee, Knoxville, TN, United States
| | - C. Iler
- Facilities Services Department, University of Tennessee, Knoxville, TN, United States
| | - S. E. DeBlander
- College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - C. M. North
- Student Health Center, University of Tennessee, Knoxville, TN, United States
| | - F. Kara-Murdoch
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States,Battelle Memorial Institute, Columbus, OH, United States
| | - C. M. Swift
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Center for Environmental Biotechnology, University of Tennessee, Knoxville, TN, United States
| | - T. C. Hazen
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States,Department of Civil and Environmental Sciences, University of Tennessee, Knoxville, 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,*Correspondence: T. C. Hazen, ✉
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54
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Wang Y, Liu P, VanTassell J, Hilton SP, Guo L, Sablon O, Wolfe M, Freeman L, Rose W, Holt C, Browning M, Bryan M, Waller L, Teunis PFM, Moe CL. When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs? WATER RESEARCH 2023; 229:119516. [PMID: 37379453 PMCID: PMC9763902 DOI: 10.1016/j.watres.2022.119516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 12/11/2022] [Accepted: 12/18/2022] [Indexed: 06/30/2023]
Abstract
Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.
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Affiliation(s)
- Yuke Wang
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Pengbo Liu
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Jamie VanTassell
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Stephen P Hilton
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Lizheng Guo
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Orlando Sablon
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Marlene Wolfe
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Lorenzo Freeman
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Wayne Rose
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Carl Holt
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Mikita Browning
- City of Atlanta Department of Watershed Management, Atlanta, GA 30303, USA
| | - Michael Bryan
- Georgia Department of Public Health, Atlanta, GA 30303, USA
| | - Lance Waller
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Peter F M Teunis
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Christine L Moe
- Center for Global Safe Water, Sanitation, and Hygiene, Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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55
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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: 7] [Impact Index Per Article: 7.0] [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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56
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Grube AM, Coleman CK, LaMontagne CD, Miller ME, Kothegal NP, Holcomb DA, Blackwood AD, Clerkin TJ, Serre ML, Engel LS, Guidry VT, Noble RT, Stewart JR. Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159996. [PMID: 36356771 PMCID: PMC9639408 DOI: 10.1016/j.scitotenv.2022.159996] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 10/28/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.
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Affiliation(s)
- Alyssa M Grube
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Collin K Coleman
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Connor D LaMontagne
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Megan E Miller
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Nikhil P Kothegal
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - David A Holcomb
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - A Denene Blackwood
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Thomas J Clerkin
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Marc L Serre
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Lawrence S Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Virginia T Guidry
- Occupational and Environmental Epidemiology Branch, NC Department of Health and Human Services, 5505 Six Forks Road, Raleigh, NC 27609, United States
| | - Rachel T Noble
- Institute of Marine Sciences, Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC 28557, United States
| | - Jill R Stewart
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States.
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57
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Sharaby Y, Gilboa Y, Alfiya Y, Sabach S, Cheruti U, Friedler E. Whole campus wastewater surveillance of SARS-CoV-2 for COVID-19 outbreak management. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2023; 87:910-923. [PMID: 36853770 DOI: 10.2166/wst.2023.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In this long-term study (eight months), a wastewater-based epidemiology program was initiated as a decision support tool for the detection and containment of COVID-19 spread in the Technion campus. The on-campus students' accommodations (∼3,300 residents) were divided into housing clusters and monitored through wastewater SARS-CoV-2 surveillance in 10 manholes. Results were used to create a 'traffic-light' scheme allowing the Technion's COVID-19 task force to track COVID-19 spatiotemporal spread on the campus, and consequently, contain it before high morbidity levels develop. Of the 523 sewage samples analysed, 87.4% were negative for SARS-CoV-2 while 11.5% were positive, corroborating morbidity information the COVID-19 task force had. For 7.6% of the SARS-CoV-2 positive samples, the task force had no information about positive resident/s. In these events, new cases were identified after the relevant residents were clinically surge tested for COVID-19. Hence, in these instances, wastewater surveillance provided early warning helping to secure the health of the campus residents by minimising COVID-19 spread. The inflammation biomarker ferritin levels in SARS-CoV-2 positive sewage samples were significantly higher than in negative ones. This may indicate that in the future, ferritin (and other biomarkers) concentrations in wastewater could serve as indicators of infectious and inflammatory disease outbreaks.
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Affiliation(s)
- Y Sharaby
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail: ; Current address: Department of Biology & Environment, University of Haifa, Oranim, Tivon, Israel
| | - Y Gilboa
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail:
| | - Y Alfiya
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail:
| | - S Sabach
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail:
| | - U Cheruti
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail:
| | - Eran Friedler
- Faculty of Civil & Environmental Engineering, Technion-Israel Institute of Technology, Haifa, Israel E-mail:
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58
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Solo-Gabriele HM, Kumar S, Abelson S, Penso J, Contreras J, Babler KM, Sharkey ME, Mantero AMA, Lamar WE, Tallon JJ, Kobetz E, Solle NS, Shukla BS, Kenney RJ, Mason CE, Schürer SC, Vidovic D, Williams SL, Grills GS, Jayaweera DT, Mirsaeidi M, Kumar N. Predicting COVID-19 cases using SARS-CoV-2 RNA in air, surface swab and wastewater samples. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159188. [PMID: 36202365 PMCID: PMC9529341 DOI: 10.1016/j.scitotenv.2022.159188] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/11/2022] [Accepted: 09/29/2022] [Indexed: 05/08/2023]
Abstract
Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples, which can serve as a noninvasive method of infectious disease surveillance. The research evaluates the efficacy of environmental monitoring of SARS-CoV-2 RNA in air, surface swabs and wastewater to predict COVID-19 cases. Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory housing roughly 500 students from March to May 2021 at the University of Miami, Coral Gables, FL. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 concentration in environmental samples was quantified using Volcano 2nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and COVID-19 cases. SARS-CoV-2 was detected in air, surface swab and wastewater samples on 52 (63.4 %), 40 (50.0 %) and 57 (68.6 %) days, respectively. On 19 (24 %) of 78 days SARS-CoV-2 was detected in all three sample types. COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100 %), 9 (81.8 %) and 8 (72.7 %) days in air, surface swab and wastewater samples, respectively. SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases and a 3-day lead indicator for a potential outbreak at the dormitory building scale. Proactive environmental surveillance of SARS-CoV-2 or other pathogens in multiple environmental media has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks within communities.
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Affiliation(s)
- Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami, Coral Gables, FL, United States of America
| | - Shelja Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Johnathon Penso
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Julio Contreras
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami, Coral Gables, FL, United States of America
| | - Mark E Sharkey
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Alejandro M A Mantero
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Walter E Lamar
- Facilities Safety & Compliance, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL, United States of America
| | - Erin Kobetz
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Natasha Schaefer Solle
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Bhavarth S Shukla
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Richard J Kenney
- Department of Housing & Residential Life, University of Miami, Coral Gables, FL, United States of America
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, United States of America
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, United States of America; Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - George S Grills
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Dushyantha T Jayaweera
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Mehdi Mirsaeidi
- Division of Pulmonary, Critical Care and Sleep, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL, United States of America
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America.
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59
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Rainey AL, Buschang K, O’Connor A, Love D, Wormington AM, Messcher RL, Loeb JC, Robinson SE, Ponder H, Waldo S, Williams R, Shapiro J, McAlister EB, Lauzardo M, Lednicky JA, Maurelli AT, Sabo-Attwood T, Bisesi J. Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies. ACS ES&T WATER 2023; 3:16-29. [PMID: 37552720 PMCID: PMC9762499 DOI: 10.1021/acsestwater.2c00275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/11/2022] [Accepted: 11/14/2022] [Indexed: 06/18/2023]
Abstract
Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.
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Affiliation(s)
- Andrew L. Rainey
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Katherine Buschang
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Amber O’Connor
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Deirdre Love
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Alexis M. Wormington
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Rebeccah L. Messcher
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Julia C. Loeb
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Sarah E. Robinson
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Hunter Ponder
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Sarah Waldo
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Roy Williams
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
| | - Jerne Shapiro
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Florida Department of
Health, Alachua County, Gainesville, Florida32641, United
States
- Department of Epidemiology, College of Public
Health and Health Professions and College of Medicine, Gainesville,
Florida32611, United States
| | | | - Michael Lauzardo
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- UF Health Screen, Test, and Protect,
University of Florida, Gainesville, Florida32611,
United States
- Department of Medicine, College of Medicine,
University of Florida, Gainesville, Florida32611,
United States
| | - John A. Lednicky
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Anthony T. Maurelli
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
| | - Tara Sabo-Attwood
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
| | - Joseph
H. Bisesi
- Department of Environmental and Global Health, College
of Public Health and Health Professions, University of Florida,
Gainesville, Florida32610, United States
- Emerging Pathogens Institute, University
of Florida, Gainesville, Florida32610, United
States
- Center for Environmental and Human Toxicology,
University of Florida, Gainesville, Florida32611,
United States
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Hopkins L, Persse D, Caton K, Ensor K, Schneider R, McCall C, Stadler LB. Citywide wastewater SARS-CoV-2 levels strongly correlated with multiple disease surveillance indicators and outcomes over three COVID-19 waves. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 855:158967. [PMID: 36162580 PMCID: PMC9507781 DOI: 10.1016/j.scitotenv.2022.158967] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Public health surveillance systems for COVID-19 are multifaceted and include multiple indicators reflective of different aspects of the burden and spread of the disease in a community. With the emergence of wastewater disease surveillance as a powerful tool to track infection dynamics of SARS-CoV-2, there is a need to integrate and validate wastewater information with existing disease surveillance systems and demonstrate how it can be used as a routine surveillance tool. A first step toward integration is showing how it relates to other disease surveillance indicators and outcomes, such as case positivity rates, syndromic surveillance data, and hospital bed use rates. Here, we present an 86-week long surveillance study that covers three major COVID-19 surges. City-wide SARS-CoV-2 RNA viral loads in wastewater were measured across 39 wastewater treatment plants and compared to other disease metrics for the city of Houston, TX. We show that wastewater levels are strongly correlated with positivity rate, syndromic surveillance rates of COVID-19 visits, and COVID-19-related general bed use rates at hospitals. We show that the relative timing of wastewater relative to each indicator shifted across the pandemic, likely due to a multitude of factors including testing availability, health-seeking behavior, and changes in viral variants. Next, we show that individual WWTPs led city-wide changes in SARS-CoV-2 viral loads, indicating a distributed monitoring system could be used to enhance the early-warning capability of a wastewater monitoring system. Finally, we describe how the results were used in real-time to inform public health response and resource allocation.
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Affiliation(s)
- Loren Hopkins
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - David Persse
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America; Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, United States of America; City of Houston Emergency Medical Services, Houston, TX, United States of America
| | - Kelsey Caton
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Katherine Ensor
- Department of Statistics, Rice University, 6100 Main Street MS 138, Houston, TX, United States of America
| | - Rebecca Schneider
- Houston Health Department, 8000 N. Stadium Dr., Houston, TX, United States of America
| | - Camille McCall
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS-519, Houston, TX, United States of America.
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61
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Li X, Zhang S, Sherchan S, Orive G, Lertxundi U, Haramoto E, Honda R, Kumar M, Arora S, Kitajima M, Jiang G. Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis. JOURNAL OF HAZARDOUS MATERIALS 2023; 441:129848. [PMID: 36067562 PMCID: PMC9420035 DOI: 10.1016/j.jhazmat.2022.129848] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 05/26/2023]
Abstract
Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.
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Affiliation(s)
- Xuan Li
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia
| | - Samendrdra Sherchan
- Department of Environmental Health Sciences, Tulane University, New Orleans, LA 70112, USA
| | - Gorka Orive
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country UPV/EHU, Paseo de la Universidad 7, Vitoria-Gasteiz 01006, Spain; Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Vitoria-Gasteiz, Spain
| | - Unax Lertxundi
- Bioaraba Health Research Institute; Osakidetza Basque Health Service, Araba Mental Health Network, Araba Psychiatric Hospital, Pharmacy Service, Vitoria-Gasteiz, Spain
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, Kofu, Japan
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, Jaipur, India
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, Hokkaido, Japan
| | - Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, Australia; Illawarra Health and Medical Research Institute (IHMRI), University of Wollongong, Wollongong, Australia.
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62
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Maryam S, Ul Haq I, Yahya G, Ul Haq M, Algammal AM, Saber S, Cavalu S. COVID-19 surveillance in wastewater: An epidemiological tool for the monitoring of SARS-CoV-2. Front Cell Infect Microbiol 2023; 12:978643. [PMID: 36683701 PMCID: PMC9854263 DOI: 10.3389/fcimb.2022.978643] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 11/03/2022] [Indexed: 01/06/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus's possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early "warning signal"; however, a lot of limitations of wastewater surveillance have also been identified.
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Affiliation(s)
- Sajida Maryam
- Department of Biosciences, The Commission on Science and Technology for Sustainable Development in the South (COMSATS) University Islamabad (CUI), Islamabad, Pakistan
| | - Ihtisham Ul Haq
- Department of Biosciences, The Commission on Science and Technology for Sustainable Development in the South (COMSATS) University Islamabad (CUI), Islamabad, Pakistan
- Department of Physical Chemistry and Polymers Technology, Silesian University of Technology, Gliwice, Poland
- Joint Doctoral School, Silesian University of Technology, Gliwice, Poland
| | - Galal Yahya
- Department of Microbiology and Immunology, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt
| | - Mehboob Ul Haq
- Department of Biosciences, The Commission on Science and Technology for Sustainable Development in the South (COMSATS) University Islamabad (CUI), Islamabad, Pakistan
| | - Abdelazeem M Algammal
- Department of Bacteriology, Immunology, and Mycology, Faculty of Veterinary Medicine, Suez Canal University, Ismailia, Egypt
| | - Sameh Saber
- Department of Pharmacology, Faculty of Pharmacy, Delta University for Science and Technology, Gamasa, Egypt
| | - Simona Cavalu
- Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania
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63
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Fralick M, Burella M, Hinz A, Mejbel HS, Guttman DS, Xing L, Moggridge J, Lapp J, Wong A, Nott C, Harris-Linton N, Kassen R, MacFadden DR. The spatial and temporal distribution of SARS-CoV-2 from the built environment of COVID-19 patient rooms: A multicentre prospective study. PLoS One 2023; 18:e0282489. [PMID: 36913370 PMCID: PMC10010533 DOI: 10.1371/journal.pone.0282489] [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] [Received: 11/24/2022] [Accepted: 02/15/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND SARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment. METHODS We conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals. RESULTS Over the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily. CONCLUSIONS We were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy.
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Affiliation(s)
- Michael Fralick
- Sinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
- Sault Area Hospital, Sault Ste. Marie, Ontario, Canada
- * E-mail:
| | - Madison Burella
- Sinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada
- Sault Area Hospital, Sault Ste. Marie, Ontario, Canada
| | - Aaron Hinz
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Hebah S. Mejbel
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - David S. Guttman
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada
- Centre for the Analysis of Genome Evolution & Function, University of Toronto, Toronto, Ontario, Canada
| | - Lydia Xing
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Jason Moggridge
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - John Lapp
- Sinai Health System, Division of General Internal Medicine, Toronto, Ontario, Canada
| | - Alex Wong
- Department of Biology, Carleton University, Ottawa, Ontario, Canada
| | - Caroline Nott
- The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Nicole Harris-Linton
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Rees Kassen
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
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Bowes DA, Driver EM, Kraberger S, Fontenele RS, Holland LA, Wright J, Johnston B, Savic S, Engstrom Newell M, Adhikari S, Kumar R, Goetz H, Binsfeld A, Nessi K, Watkins P, Mahant A, Zevitz J, Deitrick S, Brown P, Dalton R, Garcia C, Inchausti R, Holmes W, Tian XJ, Varsani A, Lim ES, Scotch M, Halden RU. Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study. THE LANCET. MICROBE 2023; 4:e29-e37. [PMID: 36493788 PMCID: PMC9725778 DOI: 10.1016/s2666-5247(22)00289-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities. METHODS In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE. FINDINGS Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases. INTERPRETATION Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio). FUNDING National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.
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Affiliation(s)
- Devin A Bowes
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Erin M Driver
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; School for Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA
| | - Simona Kraberger
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Rafaela S Fontenele
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - LaRinda A Holland
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Jillian Wright
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Bridger Johnston
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Sonja Savic
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Melanie Engstrom Newell
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA
| | - Sangeet Adhikari
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; School for Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA
| | - Rahul Kumar
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Hanah Goetz
- School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, USA
| | - Allison Binsfeld
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Kaxandra Nessi
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Payton Watkins
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Akhil Mahant
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | - Jacob Zevitz
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA
| | | | | | | | | | - Rosa Inchausti
- Strategic Management and Diversity Office, Tempe, AZ, USA
| | - Wydale Holmes
- Strategic Management and Diversity Office, Tempe, AZ, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Arvind Varsani
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Efrem S Lim
- The Biodesign Institute Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Matthew Scotch
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; College of Health Solutions, Arizona State University, Tempe, AZ, USA
| | - Rolf U Halden
- The Biodesign Institute Center for Environmental Health Engineering, Arizona State University, Tempe, AZ, USA; School for Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA; Global Futures Laboratory, Arizona State University, Tempe, AZ, USA; OneWaterOneHealth, The Arizona State University Foundation, The Biodesign Institute, Arizona State University, Tempe, AZ, USA.
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Martin M, Goethals P, Newhart K, Rhodes E, Vogel J, Stevenson B. Optimization of sewage sampling for wastewater-based epidemiology through stochastic modeling. JOURNAL OF ENGINEERING AND APPLIED SCIENCE 2023; 70:11. [PMCID: PMC9930068 DOI: 10.1186/s44147-023-00180-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
The proliferation of the SARS-CoV-2 global pandemic has brought to attention the need for epidemiological tools that can detect diseases in specific geographical areas through non-contact means. Such methods may protect those potentially infected by facilitating early quarantine policies to prevent the spread of the disease. Sampling of municipal wastewater has been studied as a plausible solution to detect pathogen spread, even from asymptomatic patients. However, many challenges exist in wastewater-based epidemiology such as identifying a representative sample for a population, determining the appropriate sample size, and establishing the right time and place for samples. In this work, a new approach to address these questions is assessed using stochastic modeling to represent wastewater sampling given a particular community of interest. Using estimates for various process parameters, inferences on the population infected are generated with Monte Carlo simulation output. A case study at the University of Oklahoma is examined to calibrate and evaluate the model output. Finally, extensions are provided for more efficient wastewater sampling campaigns in the future. This research provides greater insight into the effects of viral load, the percentage of the population infected, and sampling time on mean SARS-CoV-2 concentration through simulation. In doing so, an earlier warning of infection for a given population may be obtained and aid in reducing the spread of viruses.
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Affiliation(s)
- Max Martin
- grid.419884.80000 0001 2287 2270United States Corps of Cadets, United States Military Academy, West Point, New York, USA
| | - Paul Goethals
- grid.419884.80000 0001 2287 2270Department of Mathematical Sciences, United States Military Academy, West Point, New York, USA
| | - Kathryn Newhart
- grid.419884.80000 0001 2287 2270Department of Geography & Environmental Engineering, United States Military Academy, West Point, New York, USA
| | - Emily Rhodes
- grid.266900.b0000 0004 0447 0018School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma, USA
| | - Jason Vogel
- grid.266900.b0000 0004 0447 0018School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma, USA
| | - Bradley Stevenson
- grid.266900.b0000 0004 0447 0018Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
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66
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Armas F, Chandra F, Lee WL, Gu X, Chen H, Xiao A, Leifels M, Wuertz S, Alm EJ, Thompson J. Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era. ENVIRONMENT INTERNATIONAL 2023; 171:107718. [PMID: 36584425 PMCID: PMC9783150 DOI: 10.1016/j.envint.2022.107718] [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: 03/31/2022] [Revised: 12/16/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.
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Affiliation(s)
- Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Department of Biological Engineering, Massachusetts Institute of Technology, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
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Oh C, Zhou A, O'Brien K, Jamal Y, Wennerdahl H, Schmidt AR, Shisler JL, Jutla A, Schmidt AR, Keefer L, Brown WM, Nguyen TH. Application of neighborhood-scale wastewater-based epidemiology in low COVID-19 incidence situations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158448. [PMID: 36063927 PMCID: PMC9436825 DOI: 10.1016/j.scitotenv.2022.158448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/08/2022] [Accepted: 08/28/2022] [Indexed: 05/17/2023]
Abstract
Wastewater-based epidemiology (WBE), an emerging approach for community-wide COVID-19 surveillance, was primarily characterized at large sewersheds such as wastewater treatment plants serving a large population. Although informed public health measures can be better implemented for a small population, WBE for neighborhood-scale sewersheds is less studied and not fully understood. This study applied WBE to seven neighborhood-scale sewersheds (average population of 1471) from January to November 2021. Community testing data showed an average of 0.004 % incidence rate in these sewersheds (97 % of monitoring periods reported two or fewer daily infections). In 92 % of sewage samples, SARS-CoV-2 N gene fragments were below the limit of quantification. We statistically determined 10-2.6 as the threshold of the SARS-CoV-2 N gene concentration normalized to pepper mild mottle virus (N/PMMOV) to alert high COVID-19 incidence rate in the studied sewershed. This threshold of N/PMMOV identified neighborhood-scale outbreaks (COVID-19 incidence rate higher than 0.2 %) with 82 % sensitivity and 51 % specificity. Importantly, neighborhood-scale WBE can discern local outbreaks that would not otherwise be identified by city-scale WBE. Our findings suggest that neighborhood-scale WBE is an effective community-wide disease surveillance tool when COVID-19 incidence is maintained at a low level.
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Affiliation(s)
- Chamteut Oh
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States.
| | - Aijia Zhou
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Kate O'Brien
- School of Integrative Biology, University of Illinois Urbana-Champaign, United States
| | - Yusuf Jamal
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, United States
| | - Hayden Wennerdahl
- Illinois State Water Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, United States
| | - Arthur R Schmidt
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Joanna L Shisler
- Department of Microbiology, University of Illinois Urbana-Champaign, United States
| | - Antarpreet Jutla
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, United States
| | - Arthur R Schmidt
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States
| | - Laura Keefer
- Illinois State Water Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, United States
| | - William M Brown
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois Urbana-Champaign, United States
| | - Thanh H Nguyen
- Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, United States; Institute of Genomic Biology, University of Illinois Urbana-Champaign, United States
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68
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Jain N, Hamilton D, Mital S, Ilias A, Brinkmann M, McPhedran K. Long-term passive wastewater surveillance of SARS-CoV-2 for seven university dormitories in comparison to municipal surveillance. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158421. [PMID: 36058330 PMCID: PMC9433341 DOI: 10.1016/j.scitotenv.2022.158421] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/22/2022] [Accepted: 08/26/2022] [Indexed: 05/28/2023]
Abstract
Wastewater-based surveillance (WBS) has been an effective tool for monitoring and understanding potential SARS-CoV-2 transmission across small and large-scale communities. In this study at the University of Saskatchewan, the assessment of SARS-CoV-2 was done over eight months during the 2021-2022 academic year. Wastewater samples were collected using passive samplers that were deployed in domestic sewer lines near adjacent campus residences and extracted for viral RNA, followed by Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR). The results showed similar trends for SARS-CoV-2 detection frequencies and viral loads across university residences, the whole campus, and from related WBS at Saskatoon Wastewater Treatment Plant. The maximum daily detection frequency for seven dormitories considered was about 75 %, while maximum daily case numbers for the residences and campus-wide were about 11 and 75 people, respectively. In addition, self-reported rates of infection on campus peaked during similar time frames as increases in viral load were detected at the Saskatoon wastewater treatment plant. These similarities indicate the usefulness and cost-effectiveness of monitoring the spread of COVID-19 in small-scale communities using WBS.
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Affiliation(s)
- N Jain
- Department of Civil, Geological, and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - D Hamilton
- Department of Civil, Geological, and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - S Mital
- Department of Civil, Geological, and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - A Ilias
- Department of Civil, Geological, and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - M Brinkmann
- Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada; School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada; Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; Centre for Hydrology, University of Saskatchewan, Saskatoon, SK, Canada.
| | - K McPhedran
- Department of Civil, Geological, and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada; Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada
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69
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Li Y, Miyani B, Zhao L, Spooner M, Gentry Z, Zou Y, Rhodes G, Li H, Kaye A, Norton J, Xagoraraki I. Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158350. [PMID: 36041621 PMCID: PMC9419442 DOI: 10.1016/j.scitotenv.2022.158350] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/02/2022] [Accepted: 08/24/2022] [Indexed: 05/14/2023]
Abstract
Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.
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Affiliation(s)
- Yabing Li
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America.
| | - Brijen Miyani
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Maddie Spooner
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Zach Gentry
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Yangyang Zou
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
| | - Geoff Rhodes
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI 48824, United States of America
| | - Hui Li
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, East Lansing, MI 48824, United States of America
| | - Andrew Kaye
- CDM Smith, 535 Griswold St, Detroit, MI 48226, United States of America
| | - John Norton
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, United States of America
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, United States of America
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70
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Mangwana N, Archer E, Muller CJF, Preiser W, Wolfaardt G, Kasprzyk-Hordern B, Carstens A, Brocker L, Webster C, McCarthy D, Street R, Mathee A, Louw J, Mdhluli M, Johnson R. Sewage surveillance of SARS-CoV-2 at student campus residences in the Western Cape, South Africa. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158028. [PMID: 35973539 PMCID: PMC9375247 DOI: 10.1016/j.scitotenv.2022.158028] [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: 03/28/2022] [Revised: 07/15/2022] [Accepted: 08/10/2022] [Indexed: 05/28/2023]
Abstract
The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic capacity is limited in defined communities, posing a challenge in tracking and tracing new infections. Monitoring student residences, which are considered infection hotspots, with targeted wastewater surveillance is crucial. This study evaluated the efficacy of SARS-CoV-2 targeted wastewater surveillance for outbreak mitigation at Stellenbosch University's student residences in South Africa. Using torpedo-style passive sampling devices, wastewater samples were collected biweekly from manholes at twelve Stellenbosch University Tygerberg (SUT) campus and Stellenbosch University-Main (SUM) campus student residences. The surveillance led to an early warning detection of SARS-CoV-2 presence on campus, followed by an informed management strategy leading to restriction of student activities on campus and a delay in the onset of the third wave that was experienced throughout the country. Moreover, the study highlighted the extent of possible infections at defined locations even when a low number of confirmed coronavirus disease 2019 (COVID-19) cases were reported. The study also tracked the surge of the Delta and Omicron variants in the student residences using the Thermo Fisher TaqMan® RT-qPCR genotyping assay.
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Affiliation(s)
- Noluxabiso Mangwana
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa; Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Edward Archer
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Christo J F Muller
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa; Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardiometabolic Research in Africa, Stellenbosch University, South Africa
| | - Wolfgang Preiser
- Division of Medical Virology, Faculty of Medicine & Health Sciences, Stellenbosch University, Tygerberg, Cape Town 7505, South Africa; National Health Laboratory Services, Tygerberg Hospital, Tygerberg, Cape Town 7505, South Africa
| | - Gideon Wolfaardt
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa; Department of Chemistry and Biology, Ryerson University, Toronto, ON M5B 2K3, Canada
| | - Barbara Kasprzyk-Hordern
- Department of Chemistry, Faculty of Science, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
| | - Alno Carstens
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Ludwig Brocker
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Candice Webster
- Environment and Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg, South Africa
| | - David McCarthy
- Environmental and Public Health Microbiology Lab (EPHM LAB), Monash Infrastructure Institute, Department of Civil Engineering, Monash University, Clayton 3800, Australia
| | - Renee Street
- Environment and Health Research Unit, South African Medical Research Council (SAMRC), Durban, South Africa
| | - Angela Mathee
- Environment and Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg, South Africa
| | - Johan Louw
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
| | - Mongezi Mdhluli
- Chief Research Operations Office, South African Medical Research Council, Tygerberg 7050, South Africa
| | - Rabia Johnson
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa; Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardiometabolic Research in Africa, Stellenbosch University, South Africa.
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71
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Bonanno Ferraro G, Veneri C, Mancini P, Iaconelli M, Suffredini E, Bonadonna L, Lucentini L, Bowo-Ngandji A, Kengne-Nde C, Mbaga DS, Mahamat G, Tazokong HR, Ebogo-Belobo JT, Njouom R, Kenmoe S, La Rosa G. A State-of-the-Art Scoping Review on SARS-CoV-2 in Sewage Focusing on the Potential of Wastewater Surveillance for the Monitoring of the COVID-19 Pandemic. FOOD AND ENVIRONMENTAL VIROLOGY 2022; 14:315-354. [PMID: 34727334 PMCID: PMC8561373 DOI: 10.1007/s12560-021-09498-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 09/21/2021] [Indexed: 05/07/2023]
Abstract
The outbreak of coronavirus infectious disease-2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world. Several studies have shown that detecting SARS-CoV-2 in untreated wastewater can be a useful tool to identify new outbreaks, establish outbreak trends, and assess the prevalence of infections. On 06 May 2021, over a year into the pandemic, we conducted a scoping review aiming to summarize research data on SARS-CoV-2 in sewage. Papers dealing with raw sewage collected at wastewater treatment plants, sewer networks, septic tanks, and sludge treatment facilities were included in this review. We also reviewed studies on sewage collected in community settings such as private or municipal hospitals, healthcare facilities, nursing homes, dormitories, campuses, airports, aircraft, and cruise ships. The literature search was conducted using the electronic databases PubMed, EMBASE, and Web Science Core Collection. This comprehensive research yielded 1090 results, 66 of which met the inclusion criteria and are discussed in this review. Studies from 26 countries worldwide have investigated the occurrence of SARS-CoV-2 in sewage of different origin. The percentage of positive samples in sewage ranged from 11.6 to 100%, with viral concentrations ranging from ˂LOD to 4.6 × 108 genome copies/L. This review outlines the evidence currently available on wastewater surveillance: (i) as an early warning system capable of predicting COVID-19 outbreaks days or weeks before clinical cases; (ii) as a tool capable of establishing trends in current outbreaks; (iii) estimating the prevalence of infections; and (iv) studying SARS-CoV-2 genetic diversity. In conclusion, as a cost-effective, rapid, and reliable source of information on the spread of SARS-CoV-2 and its variants in the population, wastewater surveillance can enhance genomic and epidemiological surveillance with independent and complementary data to inform public health decision-making during the ongoing pandemic.
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Affiliation(s)
- G Bonanno Ferraro
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | | | - P Mancini
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - M Iaconelli
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - E Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - L Bonadonna
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - L Lucentini
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - A Bowo-Ngandji
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - C Kengne-Nde
- Research Monitoring and Planning Unit, National Aids Control Committee, Douala, Cameroon
| | - D S Mbaga
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - G Mahamat
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - H R Tazokong
- Department of Microbiology, The University of Yaounde I, Yaounde, Cameroon
| | - J T Ebogo-Belobo
- Medical Research Centre, Institute of Medical Research and Medicinal Plants Studies, Yaounde, Cameroon
| | - R Njouom
- Virology Department, Centre Pasteur of Cameroon, Yaounde, Cameroon
| | - S Kenmoe
- Virology Department, Centre Pasteur of Cameroon, Yaounde, Cameroon
| | - G La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy.
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72
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Sellers SC, Gosnell E, Bryant D, Belmonte S, Self S, McCarter MSJ, Kennedy K, Norman RS. Building-level wastewater surveillance of SARS-CoV-2 is associated with transmission and variant trends in a university setting. ENVIRONMENTAL RESEARCH 2022; 215:114277. [PMID: 36084672 PMCID: PMC9448636 DOI: 10.1016/j.envres.2022.114277] [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: 07/28/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 05/31/2023]
Abstract
The University of South Carolina (UofSC) was among the first universities to include building-level wastewater surveillance of SARS-CoV-2 to complement clinical testing during its reopening in the Fall 2020 semester. In the Spring 2021 semester, 24h composite wastewater samples were collected twice per week from 10 residence halls and the on-campus student isolation and quarantine building. The isolation and quarantine building served as a positive control site. The wastewater was analyzed using RT-ddPCR for the quantification of nucleocapsid genes (N1 and N2) to identify viral transmission trends within residence halls. Log10 SARS-CoV-2 RNA concentrations were compared to both new clinical cases identified in the days following wastewater collection and recovered cases returning to sites during the days preceding sample collection to test temporal and spatial associations. There was a statistically significant positive relationship between the number of cases reported from the sites during the seven-day period following wastewater sampling and the log10 viral RNA copies/L (overall IRR 1.08 (1.02, 1.16) p-value 0.0126). Additionally, a statistically significant positive relationship was identified between the number of cases returning to the residence halls after completing isolation during the seven-day period preceding wastewater sampling and the log10 viral RNA copies/L (overall 1.09 (1.01, 1.17) p-value 0.0222). The statistical significance of both identified cases and recovered return cases on log10 viral RNA copies/L in wastewater indicates the importance of including both types of clinical data in wastewater-based epidemiology (WBE) research. Genetic mutations associated with variants of concern (VOCs) were also monitored. The emergence of the Alpha variant on campus was identified, which contributed to the second wave of COVID-19 cases at UofSC. The study was able to identify sub-community transmission hotspots for targeted intervention in real-time, making WBE cost-effective and creating less of a burden on the general public compared to repeated individual testing methods.
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Affiliation(s)
- Sarah C Sellers
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Emily Gosnell
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Dillon Bryant
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Stefano Belmonte
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA
| | - Stella Self
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Green Street, Columbia, SC, USA
| | - Maggie S J McCarter
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 915 Green Street, Columbia, SC, USA
| | - Kirsten Kennedy
- Student Housing and Sustainability, Division of Student Affairs and Academic Support, University of South Carolina, 1520 Devine Street, Columbia, SC, USA
| | - R Sean Norman
- Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC, USA.
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73
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West NW, Vasquez AA, Bahmani A, Khan MF, Hartrick J, Turner CL, Shuster W, Ram JL. Sensitive detection of SARS-CoV-2 molecular markers in urban community sewersheds using automated viral RNA purification and digital droplet PCR. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157547. [PMID: 35872187 PMCID: PMC9303066 DOI: 10.1016/j.scitotenv.2022.157547] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 07/14/2022] [Accepted: 07/17/2022] [Indexed: 06/15/2023]
Abstract
Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID-19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. Standard processes for purifying viral RNA from municipal wastewater are often time-consuming and require the handling of large quantities of wastewater, negatively affecting throughput, timely reporting, and safety. We demonstrate here an automated, faster system to purify viral RNA from smaller volumes of wastewater but with increased sensitivity for detection of SARS-CoV-2 markers. We document the effectiveness of this new approach by way of comparison to the PEG/NaCl/Qiagen method prescribed by the State of Michigan for SARS-CoV-2 wastewater monitoring and show its application to several Detroit sewersheds. Specifically, compared to the PEG/NaCl/Qiagen method, viral RNA purification using the PerkinElmer Chemagic™ 360 lowered handling time, decreased the amount of wastewater required by ten-fold, increased the amount of RNA isolated per μl of final elution product by approximately five-fold, and effectively removed ddPCR inhibitors from most sewershed samples. For detection of markers on the borderline of viral detectability, we found that use of the Chemagic™ 360 enabled the measurement of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. The improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak. Applied to sewersheds in Detroit, the technique enabled more sensitive detection of SARS-CoV-2 markers with good correlation between wastewater signals and COVID-19 cases in the sewersheds. We also discuss advantages and disadvantages of several automated RNA purification systems, made by Promega, PerkinElmer, and ThermoFisher.
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Affiliation(s)
- Nicholas W West
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - Adrian A Vasquez
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA.
| | - Azadeh Bahmani
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | - Mohammed F Khan
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA
| | | | | | - William Shuster
- Department of Civil and Environmental Engineering, Wayne State University, Detroit, MI 48202, USA
| | - Jeffrey L Ram
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48201, USA
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74
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Mendoza Grijalva L, Brown B, Cauble A, Tarpeh WA. Diurnal Variability of SARS-CoV-2 RNA Concentrations in Hourly Grab Samples of Wastewater Influent during Low COVID-19 Incidence. ACS ES&T WATER 2022; 2:2125-2133. [PMID: 37552729 PMCID: PMC9063989 DOI: 10.1021/acsestwater.2c00061] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/31/2022] [Accepted: 04/06/2022] [Indexed: 06/17/2023]
Abstract
Wastewater-based epidemiology (WBE) has been widely deployed during the COVID-19 pandemic, but with limited evaluation of the utility of discrete sampling for large sewersheds and low COVID-19 incidence. In this study, SARS-CoV-2 RNA was measured in 72 consecutive hourly influent grab samples collected at a wastewater treatment plant serving nearly 500 000 residents when incidence was low (approximately 20 cases per 100 000). We characterized diurnal variability and relationships between SARS-CoV-2 RNA detection and physicochemical covariates [flow rate, total ammonia nitrogen (TAN), and total solids (TS)]. The highest detection rate observed was 82% during the first peak flow, which occurred in the early afternoon (14:00). Higher detection rates were also observed when sampling above median TAN concentrations (71%; p < 0.01; median = 40.26 mg of NH4/L). SARS-CoV-2 RNA concentrations were weakly correlated with flow rate (Kendall's τ = 0.16; p < 0.01), TAN (τ = 0.19; p < 0.05), and TS (τ = 0.18; p < 0.01), suggesting generally low RNA sewer discharges as expected at low incidence. Our results elucidated sensible adjustments to maximize detection rates, including using multiple gene targets, collecting duplicate samples, and sampling during higher flow and TAN discharges. Optimizing the lower-incidence bounds of WBE can help assess its suitability for verifying COVID-19 reemergence or eradication.
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Affiliation(s)
- Lorelay Mendoza Grijalva
- Department of Civil and Environmental Engineering,
Stanford University, Stanford, California 94305,
United States
| | - Blake Brown
- Central Contra Costa Sanitary
District, Martinez, California 94553, United
States
| | - Amanda Cauble
- Central Contra Costa Sanitary
District, Martinez, California 94553, United
States
| | - William A. Tarpeh
- Department of Civil and Environmental Engineering,
Stanford University, Stanford, California 94305,
United States
- Department of Chemical Engineering,
Stanford University, Stanford, California 94305,
United States
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75
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Bitter LC, Kibbee R, Jiménez GC, Örmeci B. Wastewater Surveillance of SARS-CoV-2 at a Canadian University Campus and the Impact of Wastewater Characteristics on Viral RNA Detection. ACS ES&T WATER 2022; 2:2034-2046. [PMID: 37552746 PMCID: PMC9128010 DOI: 10.1021/acsestwater.2c00060] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/25/2022] [Accepted: 04/27/2022] [Indexed: 05/28/2023]
Abstract
Because of the increased population density, high-risk behavior of young students, and lower vaccination rates, university campuses are considered hot spots for COVID-19 transmission. This study monitored the SARS-CoV-2 RNA levels in the wastewater of a Canadian university campus for a year to provide actionable information to safely manage COVID-19 on campus. Wastewater samples were collected from the campus sewer and residence buildings to identify changes, peaks, and hotspots and search for associations with campus events, social gatherings, long weekends, and holidays. Furthermore, the impact of wastewater parameters (total solids, volatile solids, temperature, pH, turbidity, and UV absorbance) on SARS-CoV-2 detection was investigated, and the efficiency of ultrafiltration and centrifugation concentration methods were compared. RT-qPCR was used for detecting SARS-CoV-2 RNA. Wastewater signals largely correlated positively with the clinically confirmed COVID-19 cases on campus. Long weekends and holidays were often followed by increased viral signals, and the implementation of lockdowns quickly decreased the case numbers. In spite of online teaching and restricted access to campus, the university represented a microcosm of the city and mirrored the same trends. Results indicated that the centrifugation concentration method was more sensitive for wastewater with high solids content and that the ultrafiltration concentration method was more sensitive for wastewater with low solids content. Wastewater characteristics collected from the buildings and the campus sewer were different. Statistical analysis was performed to manifest the observations. Overall, wastewater surveillance provided actionable information and was also able to bring high-risk factors and events to the attention of decision-makers, enabling timely corrective measures.
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Affiliation(s)
- Lena Carolin Bitter
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Richard Kibbee
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Gabriela C. Jiménez
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
| | - Banu Örmeci
- Department of Civil and Environmental Engineering,
Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S
5B6, Canada
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76
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Ahmed W, Smith WJM, Metcalfe S, Jackson G, Choi PM, Morrison M, Field D, Gyawali P, Bivins A, Bibby K, Simpson SL. Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater. ACS ES&T WATER 2022; 2:1871-1880. [PMID: 36380768 PMCID: PMC8848507 DOI: 10.1021/acsestwater.1c00387] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.
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Affiliation(s)
- Warish Ahmed
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Wendy J. M. Smith
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Suzanne Metcalfe
- CSIRO
Land and Water, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Greg Jackson
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Phil M. Choi
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Mary Morrison
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Daniel Field
- Water
Unit, Health Protection Branch, Prevention Division, Queensland Health, Brisbane, QLD 4001, Australia
| | - Pradip Gyawali
- Institute
of Environmental Science and Research Ltd. (ESR), Porirua 5240, New Zealand
| | - Aaron Bivins
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Kyle Bibby
- Department
of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States
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77
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Babler KM, Amirali A, Sharkey ME, Williams SL, Boone MM, Cosculluela GA, Currall BB, Grills GS, Laine J, Mason CE, Reding BD, Schürer SC, Stevenson M, Vidovic D, Solo-Gabriele HM. Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater. ACS ES&T WATER 2022; 2:2004-2013. [PMID: 37601294 PMCID: PMC10438908 DOI: 10.1021/acsestwater.2c00047] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.
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Affiliation(s)
- Kristina M. Babler
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Mark E. Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | | | - Benjamin B. Currall
- Sylvester Comprehensive Cancer Center, 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
| | - Jennifer Laine
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY USA
| | | | - Brian D. Reding
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY 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
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL USA
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78
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Rocha AY, Verbyla ME, Sant KE, Mladenov N. Detection, Quantification, and Simplified Wastewater Surveillance Model of SARS-CoV-2 RNA in the Tijuana River. ACS ES&T WATER 2022; 2:2134-2143. [PMID: 36398132 PMCID: PMC9063987 DOI: 10.1021/acsestwater.2c00062] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The COVID-19 pandemic and the detection of SARS-CoV-2 RNA in sewage has expanded global interest in wastewater surveillance. However, many underserved communities throughout the world lack improved sanitation and use informal combined sanitary and storm sewer systems. Sewage is transported via open channels, ditches, and rivers, where it mixes with surface water and/or stormwater. There is a need to develop better methods for the surveillance of pathogens such as SARS-CoV-2 RNA in this context. We developed a simplified surveillance system and monitored flow rates and concentrations of SARS-CoV-2 RNA in the Tijuana River at two locations downstream of the United States-Mexico border in California, United States. SARS-CoV-2 RNA was detected in the upstream location on six out of eight occasions, two of which were at concentrations as high as those reported in untreated wastewater from California sanitary sewer systems. The virus was not detected in any of the eight samples collected at the downstream (estuarine) sampling location, despite the consistent detection of PMMoV RNA. Synchrony was observed between the number of cases reported in Tijuana and the SARS-CoV-2 RNA concentrations measured with the CDC N1 assay when the latter were normalized by the reported flow rates in the river.
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Affiliation(s)
- Alma Y. Rocha
- Department
of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, California 92182, United States
| | - Matthew E. Verbyla
- Department
of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, California 92182, United States
| | - Karilyn E. Sant
- School
of Public Health, San Diego State University, San Diego, California 92182, United States
| | - Natalie Mladenov
- Department
of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, California 92182, United States
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79
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Strike W, Amirsoleimani A, Olaleye A, Noble A, Lewis K, Faulkner L, Backus S, Lindeman S, Eterovich K, Fraley M, Banadaki MD, Torabi S, Rockward A, Zeitlow E, Liversedge M, Keck J, Berry S. Development and Validation of a Simplified Method for Analysis of SARS-CoV-2 RNA in University Dormitories. ACS ES&T WATER 2022; 2:1984-1991. [PMID: 37552725 PMCID: PMC9115885 DOI: 10.1021/acsestwater.2c00044] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 05/26/2023]
Abstract
Over the course of the COVID-19 pandemic, wastewater surveillance has become a useful tool for describing SARS-CoV-2 prevalence in populations of varying size, from individual facilities (e.g., university residence halls, nursing homes, prisons) to entire municipalities. Wastewater analysis for SARS-CoV-2 RNA requires specialized equipment, expensive consumables, and expert staff, limiting its feasibility and scalability. Further, the extremely labile nature of viral RNA complicates sample transportation, especially in regions with limited access to reliable cold chains. Here, we present a new method for wastewater analysis, termed exclusion-based sample preparation (ESP), that substantially simplifies workflow (at least 70% decrease in time; 40% decrease in consumable usage compared with traditional techniques) by targeting the labor-intensive processing steps of RNA purification and concentration. To optimize and validate this method, we analyzed wastewater samples from residence halls at the University of Kentucky, of which 34% (44/129) contained detectible SARS-CoV-2 RNA. Although concurrent clinical testing was not comprehensive, student infections were identified in the 7 days following a positive wastewater detection in 68% of samples. This pilot study among university residence halls validated the performance and utility of the ESP method, laying the foundation for future studies in regions of the world where wastewater testing is not currently feasible.
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Affiliation(s)
- William Strike
- Departments of Biomedical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Atena Amirsoleimani
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Abisola Olaleye
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Ann Noble
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Kevin Lewis
- Environmental Quality Management, University of Kentucky, 355 Cooper Drive, Lexington, KY 40508
| | - Lee Faulkner
- Environmental Quality Management, University of Kentucky, 355 Cooper Drive, Lexington, KY 40508
| | - Spencer Backus
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Sierra Lindeman
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Katrina Eterovich
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Melicity Fraley
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Mohammad Dehghan Banadaki
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Soroosh Torabi
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Alexus Rockward
- Departments of Biomedical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
| | - Eli Zeitlow
- Department of Mechanical Engineering, University of Wisconsin-Platteville, 1 University Plaza, Platteville, WI 53818
| | - Matthew Liversedge
- Family and Community Medicine, University of Kentucky 2195 Harrodsburg Rd, Ste 125, Lexington, KY 40504
| | - James Keck
- Family and Community Medicine, University of Kentucky 2195 Harrodsburg Rd, Ste 125, Lexington, KY 40504
| | - Scott Berry
- Departments of Biomedical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
- Mechanical Engineering, University of Kentucky, 151 Ralph G. Anderson Building Lexington, KY 40506-0503
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80
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Nguyen Quoc B, Saingam P, RedCorn R, Carter JA, Jain T, Candry P, Gattuso M, Huang MLW, Greninger AL, Meschke JS, Bryan A, Winkler MKH. Case Study: Impact of Diurnal Variations and Stormwater Dilution on SARS-CoV-2 RNA Signal Intensity at Neighborhood Scale Wastewater Pumping Stations. ACS ES&T WATER 2022; 2:1964-1975. [PMID: 37552740 PMCID: PMC9261832 DOI: 10.1021/acsestwater.2c00016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 05/14/2023]
Abstract
Wastewater based epidemiology (WBE) has emerged as a tool to track the spread of SARS-CoV-2. However, sampling at wastewater treatment plants (WWTPs) cannot identify transmission hotspots within a city. Here, we sought to understand the diurnal variations (24 h) in SARS-CoV-2 RNA titers at the neighborhood level, using pump stations that serve vulnerable communities (e.g., essential workers, more diverse communities). Hourly composite samples were collected from wastewater pump stations located in (i) a residential area and (ii) a shopping district. In the residential area, SARS-CoV-2 RNA concentration (N1, N2, and E assays) varied by up to 42-fold within a 24 h period. The highest viral load was observed between 5 and 7 am, when viral RNA was not diluted by stormwater. Normalizing peak concentrations during this time window with nutrient concentrations (N and P) enabled correcting for rainfall to connect sewage to clinical cases reported in the sewershed. Data from the shopping district pump station were inconsistent, probably due to the fluctuation of customers shopping at the mall. This work indicates pump stations serving the residential area offer a narrow time period of high signal intensity that could improve the sensitivity of WBE, and tracer compounds (N, P concentration) can be used to normalize SARS-CoV-2 signals during rainfall.
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Affiliation(s)
- Bao Nguyen Quoc
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Prakit Saingam
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Raymond RedCorn
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - John A. Carter
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Tanisha Jain
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Pieter Candry
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
| | - Meghan Gattuso
- Seattle Public Utilities,
Seattle, Washington 98124, United States
| | - Meei-Li W. Huang
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - Alexander L. Greninger
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - John Scott Meschke
- Department of Environmental & Occupational Health
Sciences, University of Washington, Seattle, Washington 98105,
United States
| | - Andrew Bryan
- Dept of Laboratory Medicine and Pathology,
University of Washington, Seattle, Washington 98105,
United States
| | - Mari K. H. Winkler
- Department of Civil and Environmental Engineering,
University of Washington, Seattle, Washington 98105,
United States
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81
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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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82
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Langan LM, O’Brien M, Rundell ZC, Back JA, Ryan BJ, Chambliss CK, Norman RS, Brooks BW. Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location. ACS ES&T WATER 2022; 2:1929-1943. [PMID: 37552714 PMCID: PMC9063990 DOI: 10.1021/acsestwater.1c00476] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 05/09/2023]
Abstract
Wastewater-based epidemiology (WBE) provides an early warning and trend analysis approach for determining the presence of COVID-19 in a community and complements clinical testing in assessing the population level, even as viral loads fluctuate. Here, we evaluate combinations of two wastewater concentration methods (i.e., ultrafiltration and composite supernatant-solid), four pre-RNA extraction modifications, and three nucleic acid extraction kits using two different wastewater sampling locations. These consisted of a quarantine facility containing clinically confirmed COVID-19-positive inhabitants and a university residence hall. Of the combinations examined, composite supernatant-solid with pre-RNA extraction consisting of water concentration and RNA/DNA shield performed the best in terms of speed and sensitivity. Further, of the three nucleic acid extraction kits examined, the most variability was associated with the Qiagen kit. Focusing on the quarantine facility, viral concentrations measured in wastewater were generally significantly related to positive clinical cases, with the relationship dependent on method, modification, kit, target, and normalization, although results were variable-dependent on individual time points (Kendall's Tau-b (τ) = 0.17 to 0.6) or cumulatively (Kendall's Tau-b (τ) = -0.048 to 1). These observations can support laboratories establishing protocols to perform wastewater surveillance and monitoring efforts for COVID-19.
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Affiliation(s)
- Laura M. Langan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Megan O’Brien
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Zach C. Rundell
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Jeffrey A. Back
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Benjamin J. Ryan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
| | - C. Kevin Chambliss
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Chemistry and Biochemistry,
Baylor University, One Bear Place #97348, Waco, Texas 76798,
United States
| | - R. Sean Norman
- Environmental Health Sciences, Arnold
School of Public Health, South Carolina, 921 Assembly Street, Columbia,
South Carolina 29208, United States
| | - Bryan W. Brooks
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Institute of Biomedical Studies, Baylor
University, One Bear Place #97224, Waco, Texas 76798, United
States
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83
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Zambrana W, Catoe D, Coffman MM, Kim S, Anand A, Solis D, Sahoo MK, Pinsky BA, Bhatt AS, Boehm AB, Wolfe MK. SARS-CoV-2 RNA and N Antigen Quantification via Wastewater at the Campus Level, Building Cluster Level, and Individual-Building Level. ACS ES&T WATER 2022; 2:2025-2033. [PMID: 37552722 PMCID: PMC9128006 DOI: 10.1021/acsestwater.2c00050] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/23/2022] [Accepted: 04/27/2022] [Indexed: 05/30/2023]
Abstract
Monitoring wastewater for SARS-CoV-2 from populations smaller than those served by wastewater treatment plants may help identify small spatial areas (subsewersheds) where COVID-19 infections are present. We sampled wastewater from three nested locations with different sized populations within the same sewer network at a university campus and quantified SARS-CoV-2 RNA using reverse transcriptase droplet digital polymerase chain reaction (PCR). SARS-CoV-2 RNA concentrations and/or concentrations normalized by PMMoV were positively associated with laboratory-confirmed COVID-19 cases for both the sewershed level and the subsewershed level. We also used an antigen-based assay to detect the nucleocapsid (N) antigen from SARS-CoV-2 in wastewater samples at the sewershed level. The N antigen was regularly detected at the sewershed level, but the results were not associated with either laboratory-confirmed COVID-19 cases or SARS-CoV-2 RNA concentrations. The results of this study indicate that wastewater monitoring based on quantification of SARS-CoV-2 RNA using PCR-based methods is associated with COVID-19 cases at multiple geographic scales within the subsewershed level and can serve to aid the public health response.
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Affiliation(s)
- Winnie Zambrana
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
| | - David Catoe
- Joint Initiative for Metrology in Biology,
SLAC National Accelerator Laboratory, 2575 Sand Hill Road,
Menlo Park, California 94025, United States
| | - Mhara M. Coffman
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
| | - Sooyeol Kim
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
| | - Archana Anand
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
| | - Daniel Solis
- Department of Pathology, Stanford
University School of Medicine, Stanford, California 94305, United
States
| | - Malaya K. Sahoo
- Department of Pathology, Stanford
University School of Medicine, Stanford, California 94305, United
States
| | - Benjamin A. Pinsky
- Department of Pathology, Stanford
University School of Medicine, Stanford, California 94305, United
States
- Department of Medicine, Division of Infectious
Diseases and Geographic Medicine, Stanford University School of
Medicine, Stanford, California 94305, United
States
| | - Ami S. Bhatt
- Department of Medicine (Hematology) and Department of
Genetics, Stanford University, Stanford, California 94305,
United States
| | - Alexandria B. Boehm
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
| | - Marlene K. Wolfe
- Department of Civil and Environmental Engineering,
Stanford University, 473 Via Ortega, Stanford, California
94305, United States
- Gangarosa Department of Environmental Health, Rollins School
of Public Health, Emory University, Atlanta, Georgia 30322,
United States
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84
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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: 41] [Impact Index Per Article: 20.5] [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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85
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Kotay SM, Tanabe KO, Colosi LM, Poulter MD, Barry KE, Holstege CP, Mathers AJ, Porter MD. Building-Level Wastewater Surveillance for SARS-CoV-2 in Occupied University Dormitories as an Outbreak Forecasting Tool: One Year Case Study. ACS ES&T WATER 2022; 2:2094-2104. [PMID: 37552737 PMCID: PMC9212191 DOI: 10.1021/acsestwater.2c00057] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 06/03/2023]
Abstract
Congregate living poses one of the highest risk situations for the transmission of respiratory viruses including SARS-CoV-2. University dormitories exemplify such high-risk settings. We demonstrate the value of using building-level SARS-CoV-2 wastewater surveillance as an early warning system to inform when prevalence testing of all building occupants is warranted. Coordinated daily testing of composite wastewater samples and clinical testing in dormitories was used to prompt the screening of otherwise unrecognized infected occupants. We overlay the detection patterns in the context of regular scheduled occupant testing to validate a wastewater detection model. The trend of wastewater positivity largely aligned well with the clinical positivity and epidemiology of dormitory occupants. However, the predictive ability of wastewater-surveillance to detect new positive cases is hampered by convalescent shedding in recovered/noncontagious individuals as they return to the building. Building-level pooled wastewater-surveillance and forecasting is most productive for predicting new cases in low-prevalence instances at the community level. For higher-education facilities and other congregate living settings to remain in operation during a pandemic, a thorough surveillance-based decision-making system is vital. Building-level wastewater monitoring on a daily basis paired with regular testing of individual dormitory occupants is an effective and efficient approach for mitigating outbreaks on university campuses.
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Affiliation(s)
- Shireen M. Kotay
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Kawai O. Tanabe
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Lisa M. Colosi
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
| | - Melinda D. Poulter
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Katherine E. Barry
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Christopher P. Holstege
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
- Departments of Emergency Medicine & Pediatrics,
School of Medicine, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Amy J. Mathers
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Michael D. Porter
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
- School of Data Science, University of
Virginia, Charlottesville, Virginia 22903, United
States
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86
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de Llanos R, Cejudo-Marín R, Barneo M, Pérez-Cataluña A, Barberá-Riera M, Rebagliato M, Bellido-Blasco J, Sánchez G, Hernández F, Bijlsma L. Monitoring the evolution of SARS-CoV-2 on a Spanish university campus through wastewater analysis: A pilot project for the reopening strategy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157370. [PMID: 35842154 PMCID: PMC9278994 DOI: 10.1016/j.scitotenv.2022.157370] [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: 03/28/2022] [Revised: 07/08/2022] [Accepted: 07/10/2022] [Indexed: 06/03/2023]
Abstract
Wastewater surveillance is a fast and cost-effective tool that enables tracing of both symptomatic and asymptomatic transmission of SARS-CoV-2. In this paper, a pilot program carried out at the University Jaume I for monitoring the trends of the presence of SARS-CoV-2 in wastewater. To the best of our knowledge, this is the first such project conducted on a university campus in Spain. Wastewater samples (n = 838) were collected when students returned to campus, from October 2020 until August 2021, at a confluence sewer point and at the building level including different academic departments and services, the library, administration offices and the university student residence. It has been observed that the probability of SARS-CoV-2 RNA detection in wastewater depended on COVID-19 incidence on campus and visitors/occupants of the buildings i.e., high-, or low-traffic buildings with high or low frequency of potential contacts. Moreover, the third wave in Spain (after Christmas 2020) and an outbreak that occurred at the university student's residence could be carefully followed, allowing confirmation of the end of the outbreak. In addition, viral variants (i.e., mutations and linages) from selected time points were detected by sequencing and gave an indication of the evolution of the virus over time. The results illustrate the potential of wastewater-based epidemiology to provide an early warning for SARS-CoV-2 within the university, especially in buildings with low traffic and more defined populations, like the student residence. The strategy and experience gathered in this study will allow for implementation of improvements for reliable monitoring in the future.
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Affiliation(s)
- Rosa de Llanos
- Faculty of Health Sciences, University Jaume I, Castellón, Spain.
| | | | - Manuela Barneo
- Faculty of Health Sciences, University Jaume I, Castellón, Spain
| | - Alba Pérez-Cataluña
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - María Barberá-Riera
- Faculty of Health Sciences, University Jaume I, Castellón, Spain; Epidemiology and Public Health Center of Castellón, Spain
| | - Marisa Rebagliato
- Faculty of Health Sciences, University Jaume I, Castellón, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Bellido-Blasco
- Faculty of Health Sciences, University Jaume I, Castellón, Spain; Epidemiology and Public Health Center of Castellón, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Gloria Sánchez
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustín Escardino 7, Paterna, Valencia 46980, Spain
| | - Félix Hernández
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castellón, Spain
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castellón, Spain.
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87
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Wartell BA, Proano C, Bakalian L, Kaya D, Croft K, McCreary M, Lichtenstein N, Miske V, Arcellana P, Boyer J, Benschoten IV, Anderson M, Crabb A, Gilson S, Gourley A, Wheeler T, Trest B, Bowman G, Kjellerup BV. Implementing wastewater surveillance for SARS-CoV-2 on a university campus: Lessons learned. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2022; 94:e10807. [PMID: 36372781 PMCID: PMC9827968 DOI: 10.1002/wer.10807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/16/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
Wastewater surveillance, also known as wastewater-based epidemiology (WBE), has been successfully used to detect SARS-CoV-2 and other viruses in sewage in many locations in the United States and globally. This includes implementation of the surveillance on college and university campuses. A two-phase study was conducted during the 2020-2021 academic year to test the feasibility of a WBE system on campus and to supplement the clinical COVID-19 testing performed for the student, staff, and faculty body. The primary objective during the Fall 2020 semester was to monitor a large portion of the on-campus population and to obtain an understanding of the spreading of the SARS-CoV-2 virus. The Spring 2021 objective was focused on selected residence halls and groups of residents on campus, as this was more efficient and relevant for an effective follow-up response. Logistical problems and planning oversights initially occurred but were corrected with improved communication and experience. Many lessons were learned, including effective mapping, site planning, communication, personnel organization, and equipment management, and obtained along the way, thereby paving an opportune guide for future planning efforts. PRACTITIONER POINTS: WBE was successful in the detection of many SARS-CoV-2 variants incl. Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron. Careful planning and contingencies were essential for a successful implementation of a SARS-CoV-2 monitoring program. A surveillance program may be important for detection and monitoring of other public health relevant targets in wastewater incl. bacteria, viruses, fungi and viruses. Diverse lessons were learned incl. effective mapping, site planning, communication, personnel organization, and equipment management, thereby providing a guide for future planning efforts.
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Affiliation(s)
- Brian A. Wartell
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Camila Proano
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Lena Bakalian
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Devrim Kaya
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Kristen Croft
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Michael McCreary
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Naomi Lichtenstein
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Victoria Miske
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Patricia Arcellana
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Jessica Boyer
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Isabelle Van Benschoten
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Marya Anderson
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Andrea Crabb
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Susan Gilson
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Anthony Gourley
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Tim Wheeler
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Brian Trest
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Glynnis Bowman
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Birthe V. Kjellerup
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
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88
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Yaglom HD, Maurer M, Collins B, Hojnacki J, Monroy-Nieto J, Bowers JR, Packard S, Erickson DE, Barrand ZA, Simmons KM, Brock BN, Lim ES, Smith S, Hepp CM, Engelthaler DM. One health genomic surveillance and response to a university-based outbreak of the SARS-CoV-2 Delta AY.25 lineage, Arizona, 2021. PLoS One 2022; 17:e0272830. [PMID: 36315517 PMCID: PMC9621446 DOI: 10.1371/journal.pone.0272830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/02/2022] [Indexed: 11/06/2022] Open
Abstract
Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.
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Affiliation(s)
- Hayley D. Yaglom
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- * E-mail:
| | - Matthew Maurer
- Coconino County Health and Human Services, Flagstaff, Arizona, United States of America
| | - Brooke Collins
- Coconino County Health and Human Services, Flagstaff, Arizona, United States of America
| | - Jacob Hojnacki
- Coconino County Health and Human Services, Flagstaff, Arizona, United States of America
| | - Juan Monroy-Nieto
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - Jolene R. Bowers
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - Samuel Packard
- Coconino County Health and Human Services, Flagstaff, Arizona, United States of America
| | - Daryn E. Erickson
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - Zachary A. Barrand
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - Kyle M. Simmons
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - Breezy N. Brock
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - Efrem S. Lim
- Arizona State University, Tempe, Arizona, United States of America
| | - Sandra Smith
- Campus Health Services, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - Crystal M. Hepp
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America
| | - David M. Engelthaler
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
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Pariente MI, Segura Y, Álvarez-Torrellas S, Casas JA, de Pedro ZM, Diaz E, García J, López-Muñoz MJ, Marugán J, Mohedano AF, Molina R, Munoz M, Pablos C, Perdigón-Melón JA, Petre AL, Rodríguez JJ, Tobajas M, Martínez F. Critical review of technologies for the on-site treatment of hospital wastewater: From conventional to combined advanced processes. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 320:115769. [PMID: 35944316 DOI: 10.1016/j.jenvman.2022.115769] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 06/15/2023]
Abstract
This review aims to assess different technologies for the on-site treatment of hospital wastewater (HWW) to remove pharmaceutical compounds (PhCs) as sustances of emerging concern at a bench, pilot, and full scales from 2014 to 2020. Moreover, a rough characterisation of hospital effluents is presented. The main detected PhCs are antibiotics and psychiatric drugs, with concentrations up to 1.1 mg/L. On the one hand, regarding the presented technologies, membrane bioreactors (MBRs) are a good alternative for treating HWW with PhCs removal values higher than 80% in removing analgesics, anti-inflammatories, cardiovascular drugs, and some antibiotics. Moreover, this system has been scaled up to the pilot plant scale. However, some target compounds are still present in the treated effluent, such as psychiatric and contrast media drugs and recalcitrant antibiotics (erythromycin and sulfamethoxazole). On the other hand, ozonation effectively removes antibiotics found in the HWW (>93%), and some studies are carried out at the pilot plant scale. Even though, some families, such as the X-ray contrast media, are recalcitrant to ozone. Other advanced oxidation processes (AOPs), such as Fenton-like or UV treatments, seem very effective for removing pharmaceuticals, Antibiotic Resistance Bacteria (ARBs) and Antibiotic Resistance Genes (ARGs). However, they are not implanted at pilot plant or full scale as they usually consider extra reactants such as ozone, iron, or UV-light, making the scale-up of the processes a challenging task to treat high-loading wastewater. Thus, several examples of biological wastewater treatment methods combined with AOPs have been proposed as the better strategy to treat HWW with high removal of PhCs (generally over 98%) and ARGs/ARBs (below the detection limit) and lower spending on reactants. However, it still requires further development and optimisation of the integrated processes.
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Affiliation(s)
- M I Pariente
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain.
| | - Y Segura
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
| | - S Álvarez-Torrellas
- Department of Chemical Engineering and Materials, Universidad Complutense de Madrid, Av/ Complutense s/n, 28040, Madrid, Spain
| | - J A Casas
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - Z M de Pedro
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - E Diaz
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - J García
- Department of Chemical Engineering and Materials, Universidad Complutense de Madrid, Av/ Complutense s/n, 28040, Madrid, Spain
| | - M J López-Muñoz
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
| | - J Marugán
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
| | - A F Mohedano
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - R Molina
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
| | - M Munoz
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - C Pablos
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
| | - J A Perdigón-Melón
- Department of Analytical Chemistry, Physical Chemistry and Chemical Engineering. University of Alcalá, Ctra Madrid-Barcelona, 33,600, 28871, Alcalá de Henares, Madrid, Spain
| | - A L Petre
- Department of Analytical Chemistry, Physical Chemistry and Chemical Engineering. University of Alcalá, Ctra Madrid-Barcelona, 33,600, 28871, Alcalá de Henares, Madrid, Spain
| | - J J Rodríguez
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - M Tobajas
- Department of Chemical Engineering, Faculty of Science, Universidad Autónoma de Madrid, Campus de Cantoblanco, C/ Francisco Tomás y, Valiente, 7, 28049, Madrid, Spain
| | - F Martínez
- Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain
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90
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Kim K, Ban MJ, Kim S, Park MH, Stenstrom MK, Kang JH. Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 320:115806. [PMID: 35926387 PMCID: PMC9342910 DOI: 10.1016/j.jenvman.2022.115806] [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: 05/17/2022] [Revised: 07/15/2022] [Accepted: 07/18/2022] [Indexed: 06/15/2023]
Abstract
Wastewater-based epidemiology (WBE) is drawing increasing attention as a promising tool for an early warning of emerging infectious diseases such as COVID-19. This study demonstrated the utility of a spatial bisection method (SBM) and a global optimization algorithm (i.e., genetic algorithm, GA), to support better designing and operating a WBE program for disease surveillance and source identification. The performances of SBM and GA were compared in determining the optimal locations of sewer monitoring manholes to minimize the difference among the effective spatial monitoring scales of the selected manholes. While GA was more flexible in determining the spatial resolution of the monitoring areas, SBM allows stepwise selection of optimal sampling manholes with equiareal subcatchments and lowers computational cost. Upon detecting disease outbreaks at a regular sewer monitoring site, additional manholes within the catchment can be selected and monitored to identify source areas with a required spatial resolution. SBM offered an efficient method for rapidly searching for the optimal locations of additional sampling manholes to identify the source areas. This study provides strategic and technical elements of WBE including sampling site selection with required spatial resolution and a source identification method.
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Affiliation(s)
- Keugtae Kim
- Department of Environmental and Energy Engineering, The University of Suwon, 17 Wauan-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 18323, Republic of Korea
| | - Min Jeong Ban
- Department of Civil and Environmental Engineering, Dongguk University-Seoul, 30, Pildong-ro 1gil, Jung-gu, Seoul, 04620, Republic of Korea
| | - Sungpyo Kim
- Department of Environmental Engineering, Korea University-Sejong, 2 511, Sejong-ro, Sejong City, 30019, Republic of Korea
| | - Mi-Hyun Park
- Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Michael K Stenstrom
- Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, 90096, USA
| | - Joo-Hyon Kang
- Department of Civil and Environmental Engineering, Dongguk University-Seoul, 30, Pildong-ro 1gil, Jung-gu, Seoul, 04620, Republic of Korea.
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91
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Islam A, Hossen F, Rahman A, Sultana KF, Hasan MN, Haque A, Sosa-Hernández JE, Oyervides-Muñoz MA, Parra-Saldívar R, Ahmed T, Islam T, Dhama K, Sangkham S, Bahadur NM, Reza HM, Jakariya, Al Marzan A, Bhattacharya P, Sonne C, Ahmed F. An opinion on Wastewater-Based Epidemiological Monitoring (WBEM) with Clinical Diagnostic Test (CDT) for detecting high-prevalence areas of community COVID-19 Infections. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2022; 31:100396. [PMID: 36320818 PMCID: PMC9612100 DOI: 10.1016/j.coesh.2022.100396] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 02/17/2024]
Abstract
Wastewater-Based Epidemiological Monitoring (WBEM) is an efficient surveillance tool during the COVID-19 pandemic as it meets all requirements of a complete monitoring system including early warning, tracking the current trend, prevalence of the disease, detection of genetic diversity as well asthe up-surging SARS-CoV-2 new variants with mutations from the wastewater samples. Subsequently, Clinical Diagnostic Test is widely acknowledged as the global gold standard method for disease monitoring, despite several drawbacks such as high diagnosis cost, reporting bias, and the difficulty of tracking asymptomatic patients (silent spreaders of the COVID-19 infection who manifest nosymptoms of the disease). In this current reviewand opinion-based study, we first propose a combined approach) for detecting COVID-19 infection in communities using wastewater and clinical sample testing, which may be feasible and effective as an emerging public health tool for the long-term nationwide surveillance system. The viral concentrations in wastewater samples can be used as indicatorsto monitor ongoing SARS-CoV-2 trends, predict asymptomatic carriers, and detect COVID-19 hotspot areas, while clinical sampleshelp in detecting mostlysymptomaticindividuals for isolating positive cases in communities and validate WBEM protocol for mass vaccination including booster doses for COVID-19.
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Affiliation(s)
- Aminul Islam
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
- Advanced Molecular Lab, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, Kishoreganj, Bangladesh
| | - Foysal Hossen
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
| | - Arifur Rahman
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
| | - Khandokar Fahmida Sultana
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
| | - Mohammad Nayeem Hasan
- Department of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh
- Joint Rohingya Response Program, Food for the Hungry, Cox's Bazar, Bangladesh
| | - Atiqul Haque
- Key Lab of Animal Epidemiology and Zoonoses of Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University, Beijing, China
- Department of Microbiology, Faculty of Veterinary and Animal Science, Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200, Bangladesh
| | | | | | | | - Tanvir Ahmed
- Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh
| | | | - Kuldeep Dhama
- Indian Veterinary Research Institute, Izzatnagar-243 122, Bareilly, Uttar Pradesh, India
| | - Sarawut Sangkham
- Department of Environmental Health, School of Public Health, University of Phayao, Muang District, 56000, Phayao, Thailand
| | - Newaz Mohammed Bahadur
- Department of Applied Chemistry and Chemical Engineering, Noakhali Science and TechnologyUniversity, Noakhali-3814, Bangladesh
| | - Hasan Mahmud Reza
- Department of Pharmaceutical Sciences, North South University, Bashundhara, Dhaka, 1229, Bangladesh
| | - Jakariya
- Department of Environmental Science and Management, North South University, Bashundhara, Dhaka-1229, Bangladesh
| | - Abdullah Al Marzan
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Prosun Bhattacharya
- COVID-19 Research@KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE 114 28 Stockholm, Sweden
| | - Christian Sonne
- Department of Bioscience, Arctic Research Centre (ARC), Faculty of Science and Technology, Aarhus University, Frederiksborgvej 399, PO Box 358, 4000 Roskilde, Denmark
| | - Firoz Ahmed
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
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92
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Castro GB, Bernegossi AC, Sousa BJDO, De Lima E Silva MR, Silva FRD, Freitas BLS, Ogura AP, Corbi JJ. Global occurrence of SARS-CoV-2 in environmental aquatic matrices and its implications for sanitation and vulnerabilities in Brazil and developing countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2022; 32:2160-2199. [PMID: 34310248 DOI: 10.1080/09603123.2021.1949437] [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: 10/27/2020] [Accepted: 06/23/2021] [Indexed: 06/13/2023]
Abstract
This paper includes a systematic review of the SARS-CoV-2 occurrence in environmental aquatic matrices and a critical sanitation analysis. We discussed the interconnection of sanitation services (wastewater, water supply, solid waste, and stormwater drainage) functioning as an important network for controlling the spread of SARS-CoV-2 in waters. We collected 98 studies containing data of the SARS-CoV-2 occurrence in aquatic matrices around the world, of which 40% were from developing countries. Alongside a significant number of people infected by the virus, developing countries face socioeconomic deficiencies and insufficient public investment in infrastructure. Therefore, our study focused on highlighting solutions to provide sanitation in developing countries, considering the virus control in waters by disinfection techniques and sanitary measures, including alternatives for the vulnerable communities. The need for multilateral efforts to improve the universal coverage of sanitation services demands urgent attention in a pandemic scenario.
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Affiliation(s)
- Gleyson B Castro
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Aline C Bernegossi
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Bruno José de O Sousa
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | | | - Fernando R Da Silva
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Bárbara Luíza S Freitas
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Allan P Ogura
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
- PPG-SEA and CRHEA/SHS, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Juliano J Corbi
- Department of Hydraulic and Sanitation, São Carlos School of Engineering, University of São Paulo, São Carlos, SP, Brazil
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93
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Jiménez-Rodríguez MG, Silva-Lance F, Parra-Arroyo L, Medina-Salazar DA, Martínez-Ruiz M, Melchor-Martínez EM, Martínez-Prado MA, Iqbal HMN, Parra-Saldívar R, Barceló D, Sosa-Hernández JE. Biosensors for the detection of disease outbreaks through wastewater-based epidemiology. Trends Analyt Chem 2022; 155:116585. [PMID: 35281332 PMCID: PMC8898787 DOI: 10.1016/j.trac.2022.116585] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Wastewater-Based Epidemiology (WBE) is a novel community-wide monitoring tool that provides comprehensive real-time data of the public and environmental health status and can contribute to public health interventions, including those related to infectious disease outbreaks (e.g., the ongoing COVID-19 pandemic). Nonetheless, municipalities without centralized laboratories are likely still not able to process WBE samples. Biosensors are a potentially cost-effective solution to monitor the development of diseases through WBE to prevent local outbreaks. This review discusses the economic and technical feasibility of eighteen recently developed biosensors for the detection and monitoring of infectious disease agents in wastewater, prospecting the prevention of future pandemics.
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Affiliation(s)
| | - Fernando Silva-Lance
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico
| | - Lizeth Parra-Arroyo
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico
| | - D Alejandra Medina-Salazar
- Tecnológico Nacional de México-Instituto Tecnológico de Durango (TecNM-ITD), Department of Chemical and Biochemical Engineering, Blvd. Felipe Pescador 1830 Ote. Col. Nueva Vizcaya, Durango, Dgo, 34080, Mexico
| | - Manuel Martínez-Ruiz
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico
| | | | - María Adriana Martínez-Prado
- Tecnológico Nacional de México-Instituto Tecnológico de Durango (TecNM-ITD), Department of Chemical and Biochemical Engineering, Blvd. Felipe Pescador 1830 Ote. Col. Nueva Vizcaya, Durango, Dgo, 34080, Mexico
| | - Hafiz M N Iqbal
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, 64849, Mexico
| | | | - Damià Barceló
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Jordi Girona, 18-26, 08034, Barcelona, Spain
- Catalan Institute for Water Research (ICRA-CERCA), Parc Científic i Tecnològic de la Universitat de Girona, C/Emili Grahit, 101, Edifici H2O, 17003, Girona, Spain
- College of Environmental and Resources Sciences, Zhejiang A&F University, Hangzhou, 311300, China
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94
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Johnson W, Reeves K, Liebig J, Feula A, Butler C, Alkire M, Singh S, Litton S, O'Conor K, Jones K, Ortega N, Shimek T, Witteman J, Bjorkman KK, Mansfeldt C. Effectiveness of building-level sewage surveillance during both community-spread and sporadic-infection phases of SARS-CoV-2 in a university campus population. FEMS MICROBES 2022; 3:xtac024. [PMID: 37332508 PMCID: PMC10117889 DOI: 10.1093/femsmc/xtac024] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/27/2022] [Accepted: 09/21/2022] [Indexed: 08/29/2023] Open
Abstract
Pathogen surveillance within wastewater rapidly progressed during the SARS-CoV-2 pandemic and informed public health management. In addition to the successful monitoring of entire sewer catchment basins at the treatment facility scale, subcatchment or building-level monitoring enabled targeted support of resource deployment. However, optimizing the temporal and spatial resolution of these monitoring programs remains complex due to population dynamics and within-sewer physical, chemical, and biological processes. To address these limitations, this study explores the advancement of the building-scale network that monitored the on-campus residential population at the University of Colorado Boulder between August 2020 and May 2021 through a daily SARS-CoV-2 surveillance campaign. During the study period, SARS-CoV-2 infection prevalence transitioned from robust community spread in Fall 2020 to sporadic infections in Spring 2021. Temporally, these distinct phases enabled investigating the effectiveness of resource commitment by exploring subsets of the original daily sampling data. Spatially, select sampling sites were installed along the flow path of the pipe network, enabling the exploration of the conservation of viral concentrations within the wastewater. Infection prevalence and resource commitment for informed action displayed an inverted relationship: higher temporal and spatial resolution surveillance is more imperative during sporadic infection phases than during high prevalence periods. This relationship was reinforced when norovirus (two minor clusters) and influenza (primarily absent) were additionally surveilled at a weekly frequency. Overall, resource commitment should scale to meet the objectives of the monitoring campaign-providing a general prevalence estimate requires fewer resources than an early-warning and targeted-action monitoring framework.
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Affiliation(s)
- William Johnson
- Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, 1111 Engineering Drive, Boulder, CO 80309, United States
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Katelyn Reeves
- Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, 1111 Engineering Drive, Boulder, CO 80309, United States
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Jennifer Liebig
- BioFrontiers Institute, University of Colorado Boulder, 3415 Colorado Avenue, Boulder, CO 80303, United States
| | - Antonio Feula
- BioFrontiers Institute, University of Colorado Boulder, 3415 Colorado Avenue, Boulder, CO 80303, United States
| | - Claire Butler
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Michaela Alkire
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Samiha Singh
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Shelby Litton
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Kerry O'Conor
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Keaton Jones
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Nikolas Ortega
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Trace Shimek
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Julia Witteman
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
| | - Kristen K Bjorkman
- BioFrontiers Institute, University of Colorado Boulder, 3415 Colorado Avenue, Boulder, CO 80303, United States
| | - Cresten Mansfeldt
- Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, 1111 Engineering Drive, Boulder, CO 80309, United States
- Environmental Engineering Program, University of Colorado Boulder, 4001 Discovery Drive, Boulder, CO 80303, United States
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95
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Wastewater surveillance in smaller college communities may aid future public health initiatives. PLoS One 2022; 17:e0270385. [PMID: 36112629 PMCID: PMC9481015 DOI: 10.1371/journal.pone.0270385] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/01/2022] [Indexed: 11/26/2022] Open
Abstract
To date, the COVID-19 pandemic has resulted in over 570 million cases and over 6 million deaths worldwide. Predominant clinical testing methods, though invaluable, may create an inaccurate depiction of COVID-19 prevalence due to inadequate access, testing, or most recently under-reporting because of at-home testing. These concerns have created a need for unbiased, community-level surveillance. Wastewater-based epidemiology has been used for previous public health threats, and more recently has been established as a complementary method of SARS-CoV-2 surveillance. Here we describe the application of wastewater surveillance for SARS-CoV-2 in two university campus communities located in rural Lincoln Parish, Louisiana. This cost-effective approach is especially well suited to rural areas where limited access to testing may worsen the spread of COVID-19 and quickly exhaust the capacity of local healthcare systems. Our work demonstrates that local universities can leverage scientific resources to advance public health equity in rural areas and enhance their community involvement.
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96
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Acer PT, Kelly LM, Lover AA, Butler CS. Quantifying the Relationship between SARS-CoV-2 Wastewater Concentrations and Building-Level COVID-19 Prevalence at an Isolation Residence: A Passive Sampling Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11245. [PMID: 36141515 PMCID: PMC9517461 DOI: 10.3390/ijerph191811245] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/23/2022] [Accepted: 08/26/2022] [Indexed: 05/26/2023]
Abstract
SARS-CoV-2 RNA loads can be detected in the excreta of individuals with COVID-19 and have demonstrated positive correlations with clinical infection trends. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor community-level prevalence of infections. The majority of wastewater specimens are gathered as either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and can be challenging to maintain in cold weather, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Passive sampling can provide an affordable, practical, and scalable sampling system while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from 1 February 2021-21 May 2021. Samples (n = 64) were collected 3-5 times weekly and remained within the sewer for a median duration of 24 h. SARS-CoV-2 RNA was quantified using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform building-level public health responses.
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Affiliation(s)
- Patrick T. Acer
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst, MA 01003, USA
| | - Lauren M. Kelly
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst, MA 01003, USA
| | - Andrew A. Lover
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst, MA 01003, USA
| | - Caitlyn S. Butler
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst, MA 01003, USA
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Lu E, Ai Y, Davis A, Straathof J, Halloran K, Hull N, Winston R, Weir MH, Soller J, Bohrerova Z, Oglesbee M, Lee J. Wastewater surveillance of SARS-CoV-2 in dormitories as a part of comprehensive university campus COVID-19 monitoring. ENVIRONMENTAL RESEARCH 2022; 212:113580. [PMID: 35671797 PMCID: PMC9167806 DOI: 10.1016/j.envres.2022.113580] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/20/2022] [Accepted: 05/26/2022] [Indexed: 05/05/2023]
Abstract
Wastewater-based epidemiology is an effective tool for monitoring infectious disease spread or illicit drug use within communities. At the Ohio State University, we conducted a SARS-CoV-2 wastewater surveillance program in the 2020-2021 academic year and compared results with the university-required weekly COVID-19 saliva testing to monitor COVID-19 infection prevalence in the on-campus residential communities. The objectives of the study were to rapidly track trends in the wastewater SARS-CoV-2 gene concentrations, analyze the relationship between case numbers and wastewater signals when adjusted using human fecal viral indicator concentrations (PMMoV, crAssphage) in wastewater, and investigate the relationship of the SARS-CoV-2 gene concentrations with wastewater parameters. SARS-CoV-2 nucleocapsid and envelope (N1, N2, and E) gene concentrations, determined with reverse transcription droplet digital PCR, were used to track SARS-CoV-2 viral loads in dormitory wastewater once a week at 6 sampling sites across the campus during the fall semester in 2020. During the following spring semester, research was focused on SARS-CoV2 N2 gene concentrations at 5 sites sampled twice a week. Spearman correlations both with and without adjusting using human fecal viral indicators showed a significant correlation (p < 0.05) between human COVID-19 positive case counts and wastewater SARS-CoV-2 gene concentrations. Spearman correlations showed significant relationships between N1 gene concentrations and both TSS and turbidity, and between E gene concentrations and both pH and turbidity. These results suggest that wastewater signal increases with the census of infected individuals, in which the majority are asymptomatic, with a statistically significant (p-value <0.05) temporal correlation. The study design can be utilized as a platform for rapid trend tracking of SARS-CoV-2 variants and other diseases circulating in various communities.
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Affiliation(s)
- Emily Lu
- Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA
| | - Yuehan Ai
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA
| | - Angela Davis
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Judith Straathof
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA
| | - Kent Halloran
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Facilities Operations and Development, Environmental Health and Safety, The Ohio State University, Columbus, OH, USA
| | - Natalie Hull
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA
| | - Ryan Winston
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA; Department of Food, Agricultural, and Biological Engineering, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA
| | - Mark H Weir
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA; Sustainability Institute, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
| | | | - Zuzana Bohrerova
- Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, USA
| | - Michael Oglesbee
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
| | - Jiyoung Lee
- Department of Food Science and Technology, The Ohio State University, Columbus, OH, USA; Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA; Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA.
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98
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Mac Mahon J, Criado Monleon AJ, Gill LW, O'Sullivan JJ, Meijer WG. Wastewater-based epidemiology (WBE) for SARS-CoV-2 - A review focussing on the significance of the sewer network using a Dublin city catchment case study. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2022; 86:1402-1425. [PMID: 36178814 DOI: 10.2166/wst.2022.278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Wastewater-based epidemiology (WBE) has been employed by many countries globally since the beginning of the COVID-19 pandemic in order to assess the benefits of this surveillance tool in the context of informing public health measures. WBE has been successfully employed to detect SARS-CoV-2 at wastewater treatment plants for community-wide surveillance, as well as in smaller catchments and institutions for targeted surveillance of COVID-19. In addition, WBE has been successfully used to detect new variants, identify areas of high infection levels, as well as to detect new infection outbreaks. However, due to to the large number of inherent uncertainties in the WBE process, including the inherent intricacies of the sewer network, decay of the virus en route to a monitoring point, levels of recovery from sampling and quantification methods, levels of faecal shedding among the infected population, as well as population normalisation methods, the usefulness of wastewater samples as a means of accurately quantifying SARS-CoV-2 infection levels among a population remains less clear. The current WBE programmes in place globally will help to identify new areas of research aimed at reducing the levels of uncertainty in the WBE process, thus improving WBE as a public health monitoring tool for future pandemics. In the meantime, such programmes can provide valuable comparisons to clinical testing data and other public health metrics, as well being an effective early warning tool for new variants and new infection outbreaks. This review includes a case study of sampled wastewater from the sewer network in Dublin, Ireland, during a peak infection period of COVID-19 in the city, which evaluates the different uncertainties in the WBE process.
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Affiliation(s)
| | | | | | - John J O'Sullivan
- UCD School of Civil Engineering, UCD Dooge Centre for Water Resources Research and UCD Earth Institute, University College Dublin
| | - Wim G Meijer
- UCD School of Biomolecular & Biomedical Science, UCD Earth Institute and UCD Conway Institute, University College Dublin
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99
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Lee WL, Gu X, Armas F, Leifels M, Wu F, Chandra F, Chua FJD, Syenina A, Chen H, Cheng D, Ooi EE, Wuertz S, Alm EJ, Thompson J. Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities. WATER RESEARCH 2022; 223:118904. [PMID: 36007397 DOI: 10.1016/j.watres.2022.118904] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 07/19/2022] [Accepted: 07/23/2022] [Indexed: 05/21/2023]
Abstract
Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.
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Affiliation(s)
- Wei Lin Lee
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Xiaoqiong Gu
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Federica Armas
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Mats Leifels
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Fuqing Wu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, Center for Infectious Disease, University of Texas School of Public Health, Houston, TX, USA
| | - Franciscus Chandra
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Feng Jun Desmond Chua
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Ayesa Syenina
- Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore
| | - Hongjie Chen
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Dan Cheng
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore
| | - Eng Eong Ooi
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Program in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Viral Research and Experimental Medicine Centre (ViREMiCS), SingHealth Duke-NUS Academic Medical Centre, Singapore 169856, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore
| | - Stefan Wuertz
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Eric J Alm
- Antimicrobial Resistance Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore 138602, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore 637551, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore 637459, Singapore.
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100
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Al Huraimel K, Alhosani M, Gopalani H, Kunhabdulla S, Stietiya MH. Elucidating the role of environmental management of forests, air quality, solid waste and wastewater on the dissemination of SARS-CoV-2. HYGIENE AND ENVIRONMENTAL HEALTH ADVANCES 2022; 3:100006. [PMID: 37519421 PMCID: PMC9095661 DOI: 10.1016/j.heha.2022.100006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 04/13/2022] [Accepted: 04/30/2022] [Indexed: 11/29/2022]
Abstract
The increasing frequency of zoonotic diseases is amongst several catastrophic repercussions of inadequate environmental management. Emergence, prevalence, and lethality of zoonotic diseases is intrinsically linked to environmental management which are currently at a destructive level globally. The effects of these links are complicated and interdependent, creating an urgent need of elucidating the role of environmental mismanagement to improve our resilience to future pandemics. This review focused on the pertinent role of forests, outdoor air, indoor air, solid waste and wastewater management in COVID-19 dissemination to analyze the opportunities prevailing to control infectious diseases considering relevant data from previous disease outbreaks. Global forest management is currently detrimental and hotspots of forest fragmentation have demonstrated to result in zoonotic disease emergences. Deforestation is reported to increase susceptibility to COVID-19 due to wildfire induced pollution and loss of forest ecosystem services. Detection of SARS-CoV-2 like viruses in multiple animal species also point to the impacts of biodiversity loss and forest fragmentation in relation to COVID-19. Available literature on air quality and COVID-19 have provided insights into the potential of air pollutants acting as plausible virus carrier and aggravating immune responses and expression of ACE2 receptors. SARS-CoV-2 is detected in outdoor air, indoor air, solid waste, wastewater and shown to prevail on solid surfaces and aerosols for prolonged hours. Furthermore, lack of protection measures and safe disposal options in waste management are evoking concerns especially in underdeveloped countries due to high infectivity of SARS-CoV-2. Inadequate legal framework and non-adherence to environmental regulations were observed to aggravate the postulated risks and vulnerability to future waves of pandemics. Our understanding underlines the urgent need to reinforce the fragile status of global environmental management systems through the development of strict legislative frameworks and enforcement by providing institutional, financial and technical supports.
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Affiliation(s)
- Khaled Al Huraimel
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Mohamed Alhosani
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Hetasha Gopalani
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Shabana Kunhabdulla
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Mohammed Hashem Stietiya
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
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