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Wang Y, Ni G, Tian W, Wang H, Li J, Thai P, Choi PM, Jackson G, Hu S, Yang B, Guo J. Wastewater tiling amplicon sequencing in sentinel sites reveals longitudinal dynamics of SARS-CoV-2 variants prevalence. WATER RESEARCH X 2024; 23:100224. [PMID: 38711798 PMCID: PMC11070618 DOI: 10.1016/j.wroa.2024.100224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/17/2024] [Accepted: 04/19/2024] [Indexed: 05/08/2024]
Abstract
The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.
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Affiliation(s)
- Yu Wang
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Gaofeng Ni
- Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
| | - Wei Tian
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Haofei Wang
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Jiaying Li
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Queensland, Australia
| | - Phong Thai
- Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane, Queensland, Australia
| | - Phil M. Choi
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Brisbane, Queensland, Australia
| | - Greg Jackson
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Brisbane, Queensland, Australia
| | - Shihu Hu
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
| | - Bicheng Yang
- MGI Australia Pty Ltd, 300 Herston Road, Herston, Brisbane, QLD 4006, Australia
| | - Jianhua Guo
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia
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2
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Amirali A, Babler KM, Sharkey ME, Beaver CC, Boone MM, Comerford S, Cooper D, Currall BB, Goodman KW, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Mason CE, Reding BD, Roca MA, Ryon K, Schürer SC, Shukla BS, Solle NS, Stevenson M, Tallon JJ, Vidović D, Williams SL, Yin X, Solo-Gabriele HM. Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170452. [PMID: 38296085 PMCID: PMC10923133 DOI: 10.1016/j.scitotenv.2024.170452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/30/2023] [Accepted: 01/19/2024] [Indexed: 02/07/2024]
Abstract
Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.
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Affiliation(s)
- Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Cynthia C Beaver
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Melinda M Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samuel Comerford
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | | | - Benjamin B Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Kenneth W Goodman
- Frost Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA; Institute for Bioethics and Health Policy, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter E Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA
| | - Bhavarth S Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Natasha Schaefer Solle
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Mario Stevenson
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dušica Vidović
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Xue Yin
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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3
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Haskell BR, Dhiyebi HA, Srikanthan N, Bragg LM, Parker WJ, Giesy JP, Servos MR. Implementing an adaptive, two-tiered SARS-CoV-2 wastewater surveillance program on a university campus using passive sampling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168998. [PMID: 38040360 DOI: 10.1016/j.scitotenv.2023.168998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
Building-level wastewater-based surveillance (WBS) has been increasingly applied upstream from wastewater treatment plants to conduct targeted monitoring for SARS-CoV-2. In this study, a two-tiered, trigger-based wastewater surveillance program was developed on a university campus to monitor dormitory wastewater. The objective was to determine if passive sampling with cotton gauze as a sampling medium could be used to support institution-level public health action. Two nucleocapsid gene targets (N1 and N2) of SARS-CoV-2 as well as the endogenous fecal indicator pepper mild mottle virus (PMMoV) were quantified using RT-qPCR. >500 samples were analyzed during two contrasting surveillance periods. In the Fall of 2021 community viral burden was low and a tiered sampling network was able to isolate individual clinical cases at the building-scale. In the Winter of 2022 wastewater signals were quickly elevated by the emergence of the highly transmissible SARS-CoV-2 Omicron (B.1.1.529) variant. Prevalence of SARS-CoV-2 shifted surveillance objectives from isolating cases to monitoring trends, revealing both the benefits and limitations of a tiered surveillance design under different public health situations. Normalization of SARS-CoV-2 by PMMoV was not reflective of upstream population differences, suggesting saturation of the material occurred during the exposure period. The passive sampling method detected nearly all known clinical cases and in one instance was able to identify one pre-symptomatic individual days prior to confirmation by clinical test. Comparisons between campus samplers and municipal wastewater influent suggests that the spread of COVID-19 on the campus was similar to that of the broader community. The results demonstrate that passive sampling is an effective tool that can produce semi-quantitative data capable of tracking temporal trends to guide targeted public health decision-making at an institutional level. Practitioners of WBS can utilize these results to inform surveillance program designs that prioritize efficient resource use and rapid reporting.
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Affiliation(s)
- Blake R Haskell
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Hadi A Dhiyebi
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Nivetha Srikanthan
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada
| | - Leslie M Bragg
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
| | - Wayne J Parker
- Department of Civil and Environmental Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada.
| | - John P Giesy
- Toxicology Centre, University of Saskatchewan, 44 Campus Dr., Saskatoon, Saskatchewan S7N 5B3, Canada; Department of Environmental Science, Baylor University, 1 Bear Trail, Waco, TX 76798, USA
| | - Mark R Servos
- Department of Biology, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
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4
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Vo V, Harrington A, Chang CL, Baker H, Moshi MA, Ghani N, Itorralba JY, Tillett RL, Dahlmann E, Basazinew N, Gu R, Familara TD, Boss S, Vanderford F, Ghani M, Tang AJ, Matthews A, Papp K, Khan E, Koutras C, Kan HY, Lockett C, Gerrity D, Oh EC. Identification and genome sequencing of an influenza H3N2 variant in wastewater from elementary schools during a surge of influenza A cases in Las Vegas, Nevada. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162058. [PMID: 36758698 PMCID: PMC9909754 DOI: 10.1016/j.scitotenv.2023.162058] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/02/2023] [Accepted: 02/02/2023] [Indexed: 05/25/2023]
Abstract
Real-time surveillance of infectious diseases at schools or in communities is often hampered by delays in reporting due to resource limitations and infrastructure issues. By incorporating quantitative PCR and genome sequencing, wastewater surveillance has been an effective complement to public health surveillance at the community and building-scale for pathogens such as poliovirus, SARS-CoV-2, and even the monkeypox virus. In this study, we asked whether wastewater surveillance programs at elementary schools could be leveraged to detect RNA from influenza viruses shed in wastewater. We monitored for influenza A and B viral RNA in wastewater from six elementary schools from January to May 2022. Quantitative PCR led to the identification of influenza A viral RNA at three schools, which coincided with the lifting of COVID-19 restrictions and a surge in influenza A infections in Las Vegas, Nevada, USA. We performed genome sequencing of wastewater RNA, leading to the identification of a 2021-2022 vaccine-resistant influenza A (H3N2) 3C.2a1b.2a.2 subclade. We next tested wastewater samples from a treatment plant that serviced the elementary schools, but we were unable to detect the presence of influenza A/B RNA. Together, our results demonstrate the utility of near-source wastewater surveillance for the detection of local influenza transmission in schools, which has the potential to be investigated further with paired school-level influenza incidence data.
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Affiliation(s)
- Van Vo
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Anthony Harrington
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Ching-Lan Chang
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Hayley Baker
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Michael A Moshi
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nabih Ghani
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Jose Yani Itorralba
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard L Tillett
- Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Elizabeth Dahlmann
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Natnael Basazinew
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Richard Gu
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Tiffany D Familara
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Sage Boss
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Fritz Vanderford
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Moonis Ghani
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Austin J Tang
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Alice Matthews
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Katerina Papp
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA
| | - Eakalak Khan
- Department of Civil and Environmental Engineering and Construction, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Carolina Koutras
- R-Zero Systems, Inc., 345 W Bearcat Dr Suite #100, South Salt Lake, UT 84115, USA
| | - Horng-Yuan Kan
- Southern Nevada Health District, Las Vegas, NV 89106, USA
| | | | - Daniel Gerrity
- Southern Nevada Water Authority, P.O. Box 99954, Las Vegas, NV 89193, USA
| | - Edwin C Oh
- Laboratory of Neurogenetics and Precision Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Nevada Institute of Personalized Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA; Department of Internal Medicine, UNLV School of Medicine, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
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5
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Lopez Marin MA, Zdenkova K, Bartackova J, Cermakova E, Dostalkova A, Demnerova K, Vavruskova L, Novakova Z, Sykora P, Rumlova M, Bartacek J. Monitoring COVID-19 spread in selected Prague's schools based on the presence of SARS-CoV-2 RNA in wastewater. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:161935. [PMID: 36731569 PMCID: PMC9886433 DOI: 10.1016/j.scitotenv.2023.161935] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 01/13/2023] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
The COVID-19 pandemic has demanded a broad range of techniques to better monitor its extent. Owing to its consistency, non-invasiveness, and cost effectiveness, wastewater-based epidemiology has emerged as a relevant approach to monitor the pandemic's course. In this work, we analyzed the extent of the COVID-19 pandemic in five primary schools in Prague, the Czech Republic, and how different preventive measures impact the presence of SARS-CoV-2 RNA copy numbers in wastewaters. Copy numbers were measured by reverse transcription-multiplex quantitative real-time PCR. These copy numbers were compared to the number of infected individuals in each school identified through regular clinical tests. Each school had a different monitoring regime and subsequent application of preventive measures to thwart the spread of COVID-19. The schools that constantly identified and swiftly quarantined infected individuals exhibited persistently low amounts of SARS-CoV-2 RNA copies in their wastewaters. In one school, a consistent monitoring of infected individuals, coupled with a delayed action to quarantine, allowed for the estimation of a linear model to predict the number of infected individuals based on the presence of SARS-CoV-2 RNA in the wastewater. The results show the importance of case detection and quarantining to stop the spread of the pandemic and its impact on the presence of SARS-CoV-2 RNA in wastewaters. This work also shows that wastewater-based epidemiological models can be reliably used even in small water catchments, but difficulties arise to fit models due to the nonconstant input of viral particles into the wastewater systems.
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Affiliation(s)
- Marco A Lopez Marin
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czechia
| | - K Zdenkova
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czechia.
| | - J Bartackova
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czechia
| | - E Cermakova
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czechia
| | - A Dostalkova
- Department of Biotechnology, University of Chemistry and Technology Prague, Czechia
| | - K Demnerova
- Department of Biochemistry and Microbiology, University of Chemistry and Technology Prague, Czechia
| | | | - Z Novakova
- Prazske vodovody a kanalizace, a.s., Czechia
| | - P Sykora
- Prazske vodovody a kanalizace, a.s., Czechia
| | - M Rumlova
- Department of Biotechnology, University of Chemistry and Technology Prague, Czechia
| | - J Bartacek
- Department of Water Technology and Environmental Engineering, University of Chemistry and Technology Prague, Czechia
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6
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Swift CL, Isanovic M, Correa Velez KE, Norman RS. SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales. ENVIRONMENTAL ADVANCES 2023; 11:100347. [PMID: 36718477 PMCID: PMC9876004 DOI: 10.1016/j.envadv.2023.100347] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/17/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.
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Affiliation(s)
- Candice L Swift
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - Mirza Isanovic
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - Karlen E Correa Velez
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
| | - R Sean Norman
- Department of Environmental Health Sciences, University of South Carolina, 921 Assembly Street, Suite 401, Columbia, SC 29208, USA
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7
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Lucansky V, Samec M, Burjanivova T, Lukacova E, Kolkova Z, Holubekova V, Turyova E, Hornakova A, Zaborsky T, Podlesniy P, Reizigova L, Dankova Z, Novakova E, Pecova R, Calkovska A, Halasova E. Comparison of the methods for isolation and detection of SARS-CoV-2 RNA in municipal wastewater. Front Public Health 2023; 11:1116636. [PMID: 36960362 PMCID: PMC10028190 DOI: 10.3389/fpubh.2023.1116636] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/17/2023] [Indexed: 03/09/2023] Open
Abstract
Introduction Coronavirus SARS-CoV-2 is a causative agent responsible for the current global pandemic situation known as COVID-19. Clinical manifestations of COVID-19 include a wide range of symptoms from mild (i.e., cough, fever, dyspnea) to severe pneumonia-like respiratory symptoms. SARS-CoV-2 has been demonstrated to be detectable in the stool of COVID-19 patients. Waste-based epidemiology (WBE) has been shown as a promising approach for early detection and monitoring of SARS-CoV-2 in the local population performed via collection, isolation, and detection of viral pathogens from environmental sources. Methods In order to select the optimal protocol for monitoring the COVID-19 epidemiological situation in region Turiec, Slovakia, we (1) compared methods for SARS-CoV-2 separation and isolation, including virus precipitation by polyethylene glycol (PEG), virus purification via ultrafiltration (Vivaspin®) and subsequent isolation by NucleoSpin RNA Virus kit (Macherey-Nagel), and direct isolation from wastewater (Zymo Environ Water RNA Kit); (2) evaluated the impact of water freezing on SARS- CoV-2 separation, isolation, and detection; (3) evaluated the role of wastewater filtration on virus stability; and (4) determined appropriate methods including reverse transcription-droplet digital PCR (RT-ddPCR) and real-time quantitative polymerase chain reaction (RT-qPCR) (targeting the same genes, i.e., RdRp and gene E) for quantitative detection of SARS-CoV-2 in wastewater samples. Results (1) Usage of Zymo Environ Water RNA Kit provided superior quality of isolated RNA in comparison with both ultracentrifugation and PEG precipitation. (2) Freezing of wastewater samples significantly reduces the RNA yield. (3) Filtering is counterproductive when Zymo Environ Water RNA Kit is used. (4) According to the specificity and sensitivity, the RT-ddPCR outperforms RT-qPCR. Discussion The results of our study suggest that WBE is a valuable early warning alert and represents a non-invasive approach to monitor viral pathogens, thus protects public health on a regional and national level. In addition, we have shown that the sensitivity of testing the samples with a nearer detection limit can be improved by selecting the appropriate combination of enrichment, isolation, and detection methods.
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Affiliation(s)
- Vincent Lucansky
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
| | - Marek Samec
- Department of Pathophysiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Tatiana Burjanivova
- Department of Molecular Biology and Genomics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Eva Lukacova
- Department of Molecular Biology and Genomics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Zuzana Kolkova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
| | - Veronika Holubekova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
| | - Eva Turyova
- Department of Molecular Biology and Genomics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Andrea Hornakova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
| | - Tibor Zaborsky
- RÚVZ (Regional Office of Public Health), Martin, Slovakia
| | - Petar Podlesniy
- Centro Investigacion Biomedica en Red Enfermedades Neurodegenerativas (CiberNed), Madrid, Spain
| | - Lenka Reizigova
- Center for Microbiology and Infection Prevention, Department of Laboratory Medicine, Faculty of Health Care and Social Work, Trnava University, Trnava, Slovakia
| | - Zuzana Dankova
- Biobank for Cancer and Rare Diseases, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
| | - Elena Novakova
- Department of Microbiology and Immunology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Renata Pecova
- Department of Pathophysiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Andrea Calkovska
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Erika Halasova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin (JFMED CU), Comenius University in Bratislava, Martin, Slovakia
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