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Pasha ABT, Kotlarz N, Holcomb D, Reckling S, Kays J, Bailey E, Guidry V, Christensen A, Berkowitz S, Engel LS, de Los Reyes F, Harris A. Monitoring SARS-CoV-2 RNA in wastewater from a shared septic system and sub-sewershed sites to expand COVID-19 disease surveillance. JOURNAL OF WATER AND HEALTH 2024; 22:978-992. [PMID: 38935450 DOI: 10.2166/wh.2024.303] [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: 10/10/2023] [Accepted: 02/21/2024] [Indexed: 06/29/2024]
Abstract
Wastewater-based epidemiology has expanded as a tool for collecting COVID-19 surveillance data, but there is limited information on the feasibility of this form of surveillance within decentralized wastewater systems (e.g., septic systems). This study assessed SARS-CoV-2 RNA concentrations in wastewater samples from a septic system servicing a mobile home park (66 households) and from two pumping stations serving a similarly sized (71 households) and a larger (1,000 households) neighborhood within a nearby sewershed over 35 weeks in 2020. Also, raw wastewater from a hospital in the same sewershed was sampled. The mobile home park samples had the highest detection frequency (39/39 days) and mean concentration of SARS-CoV-2 RNA (2.7 × 107 gene copies/person/day for the N1) among the four sampling sites. N1 gene and N2 gene copies were highly correlated across mobile home park samples (Pearson's r = 0.93, p < 0.0001). In the larger neighborhood, new COVID-19 cases were reported every week during the sampling period; however, we detected SARS-CoV-2 RNA in 12% of the corresponding wastewater samples. The results of this study suggest that sampling from decentralized wastewater infrastructure can be used for continuous monitoring of SARS-CoV-2 infections.
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Affiliation(s)
- A B Tanvir Pasha
- Department of Civil, Construction and Environmental Engineering, North Carolina State University (NC State), 915 Partners Way, Raleigh, NC 27606, USA
| | - Nadine Kotlarz
- Center for Human Health and the Environment, NC State, Raleigh, NC, USA
| | - David Holcomb
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Stacie Reckling
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC, USA
| | - Judith Kays
- Department of Civil, Construction and Environmental Engineering, North Carolina State University (NC State), 915 Partners Way, Raleigh, NC 27606, USA
| | | | - Virginia Guidry
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC, USA
| | - Ariel Christensen
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC, USA
| | - Steven Berkowitz
- Division of Public Health, North Carolina Department of Health and Human Services, Raleigh, NC, USA
| | - Lawrence S Engel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Francis de Los Reyes
- Department of Civil, Construction and Environmental Engineering, North Carolina State University (NC State), 915 Partners Way, Raleigh, NC 27606, USA
| | - Angela Harris
- Department of Civil, Construction and Environmental Engineering, North Carolina State University (NC State), 915 Partners Way, Raleigh, NC 27606, USA E-mail:
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2
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Li L, Haak L, Carine M, Pagilla KR. Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics. Heliyon 2024; 10:e29462. [PMID: 38638959 PMCID: PMC11024598 DOI: 10.1016/j.heliyon.2024.e29462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/20/2024] Open
Abstract
This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends.
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Affiliation(s)
- Lin Li
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
| | - Krishna R. Pagilla
- Department of Civil and Environmental Engineering, University of Nevada Reno, Reno, NV, 89557, USA
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Carine MR, Pagilla KR. A mass balance approach for quantifying the role of natural decay and fate mechanisms on SARS-CoV-2 genetic marker removal during water reclamation. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2024; 96:e11015. [PMID: 38599573 DOI: 10.1002/wer.11015] [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: 12/08/2023] [Revised: 02/06/2024] [Accepted: 02/28/2024] [Indexed: 04/12/2024]
Abstract
The recent SARS-CoV-2 outbreak yielded substantial data regarding virus fate and prevalence at water reclamation facilities (WRFs), identifying influential factors as natural decay, adsorption, light, pH, salinity, and antagonistic microorganisms. However, no studies have quantified the impact of these factors in full scale WRFs. Utilizing a mass balance approach, we assessed the impact of natural decay and other fate mechanisms on genetic marker removal during water reclamation, through the use of sludge and wastewater genetic marker loading estimates. Results indicated negligible removal of genetic markers during P/PT (primary effluent (PE) p value: 0.267; preliminary and primary treatment (P/PT) accumulation p value: 0.904; and thickened primary sludge (TPS) p value: 0.076) indicating no contribution of natural decay and other fate mechanisms toward removal in P/PT. Comparably, adsorption and decomposition was found to be the dominant pathway for genetic marker removal (thickened waste activated sludge (TWAS) log loading 9.75 log10 GC/day); however, no estimation of log genetic marker accumulation could be carried out due to high detections in TWAS. PRACTITIONER POINTS: The mass balance approach suggested that the contribution of natural decay and other fate mechanisms to virus removal during wastewater treatment are negligible compared with adsorption and decomposition in P/PT (p value: 0.904). During (P/PT), a higher viral load remained in the (PE) (14.16 log10 GC/day) compared with TPS (13.83 log10 GC/day); however, no statistical difference was observed (p value: 0.280) indicting that adsorption/decomposition most probably did not occur. In secondary treatment (ST), viral genetic markers in TWAS were consistently detected (13.41 log10 GC/day) compared with secondary effluent (SE), indicating that longer HRT and the potential presence of extracellular polymeric substance-containing enriched biomass enabled adsorption/decomposition. Estimations of total solids and volatile solids for TPS and TWAS indicated that adsorption affinity was different between solids sampling locations (p value: <0.0001).
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Affiliation(s)
- Madeline R Carine
- Department of Civil and Environmental Engineering, University of Nevada, Reno, Nevada, USA
| | - Krishna R Pagilla
- Department of Civil and Environmental Engineering, University of Nevada, Reno, Nevada, USA
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4
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Chen C, Kaur G, Adiga A, Espinoza B, Venkatramanan S, Warren A, Lewis B, Crow J, Singh R, Lorentz A, Toney D, Marathe M. Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey. ARXIV 2024:arXiv:2403.15291v1. [PMID: 38562450 PMCID: PMC10984000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively track the prevalence of COVID-19 within communities. The traditional way to estimate the disease prevalence is to estimate from reported clinical test data or surveys. However, the coverage of clinical tests is often limited and the tests can be labor-intensive, requires reliable and timely results, and consistent diagnostic and reporting criteria. Recent studies revealed that patients who are diagnosed with COVID-19 often undergo fecal shedding of SARS-CoV-2 virus into wastewater, which makes wastewater-based epidemiology (WBE) for COVID-19 surveillance a promising approach to complement traditional clinical testing. In this paper, we survey the existing literature regarding WBE for COVID-19 surveillance and summarize the current advances in the area. Specifically, we have covered the key aspects of wastewater sampling, sample testing, and presented a comprehensive and organized summary of wastewater data analytical methods. Finally, we provide the open challenges on current wastewater-based COVID-19 surveillance studies, aiming to encourage new ideas to advance the development of effective wastewater-based surveillance systems for general infectious diseases.
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Affiliation(s)
- Chen Chen
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Gursharn Kaur
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Aniruddha Adiga
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Baltazar Espinoza
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Srinivasan Venkatramanan
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Andrew Warren
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Bryan Lewis
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
| | - Justin Crow
- Virginia Department of Health, Richmond, 23219, United States
| | - Rekha Singh
- Virginia Department of Health, Richmond, 23219, United States
| | - Alexandra Lorentz
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Denise Toney
- Division of Consolidated Laboratory Services, Department of General Services, Richmond, 23219, United States
| | - Madhav Marathe
- Biocomplexity Institute and Initiative, University of Virginia, Charlottesville, 22904, United States
- Department of Computer Science, University of Virginia, Charlottesville, 22904, United States
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5
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Tran DPH, You BC, Liu CW, Chen YN, Wang YF, Chung SN, Lee JJ, You SJ. Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:11576-11590. [PMID: 38221556 DOI: 10.1007/s11356-023-31769-x] [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: 01/23/2023] [Accepted: 12/25/2023] [Indexed: 01/16/2024]
Abstract
Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants. Wastewater-based epidemiology (WBE) is considered a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman's r = 0.23-0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTP influent (> 90%). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hotspot model combined with the geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from the sewer system. In addition, socio-economic factors, namely, population density, land use, and income tax were successfully identified as the potential drivers which substantially affected the onset of the COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also to other epidemic issues in the future.
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Affiliation(s)
- Duyen Phuc-Hanh Tran
- Department of Civil Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Bo-Cheng You
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Chen-Wuing Liu
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Yi-Ning Chen
- Department of Bioscience Technology, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Ya-Fen Wang
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China
| | - Shu-Nu Chung
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Jin-Jing Lee
- Department of Water Resource, Taoyuan City Government, Taoyuan City, 320, Taiwan, Republic of China
| | - Sheng-Jie You
- Center for Environmental Risk Management, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China.
- Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan City, 320, Taiwan, Republic of China.
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6
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Baz Lomba JA, Pires J, Myrmel M, Arnø JK, Madslien EH, Langlete P, Amato E, Hyllestad S. Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic. JOURNAL OF WATER AND HEALTH 2024; 22:197-234. [PMID: 38295081 PMCID: wh_2023_279 DOI: 10.2166/wh.2023.279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.
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Affiliation(s)
- Jose Antonio Baz Lomba
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway E-mail:
| | - João Pires
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway; ECDC fellowship Programme, Public Health Microbiology path (EUPHEM), European Centre for Disease Prevention and Control (ECDC), Solna, Sweden
| | - Mette Myrmel
- Faculty of Veterinary Medicine, Virology Unit, Norwegian University of Life Science (NMBU), Oslo, Norway
| | - Jorunn Karterud Arnø
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Elisabeth Henie Madslien
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Petter Langlete
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Ettore Amato
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
| | - Susanne Hyllestad
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway
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7
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Fu Y, Liu Y, Song W, Yang D, Wu W, Lin J, Yang X, Zeng J, Rong L, Xia J, Lei H, Yang R, Zhang M, Liao Y. Early monitoring-to-warning Internet of Things system for emerging infectious diseases via networking of light-triggered point-of-care testing devices. EXPLORATION (BEIJING, CHINA) 2023; 3:20230028. [PMID: 38264687 PMCID: PMC10742204 DOI: 10.1002/exp.20230028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 07/31/2023] [Indexed: 01/25/2024]
Abstract
Early monitoring and warning arrangements are effective ways to distinguish infectious agents and control the spread of epidemic diseases. Current testing technologies, which cannot achieve rapid detection in the field, have a risk of slowing down the response time to the disease. In addition, there is still no epidemic surveillance system, implementing prevention and control measures is slow and inefficient. Motivated by these clinical needs, a sample-to-answer genetic diagnosis platform based on light-controlled capillary modified with a photocleavable linker is first developed, which could perform nucleic acid separation and release by light irradiation in less than 30 seconds. Then, on site polymerase chain reaction was performed in a handheld closed-loop convective system. Test reports are available within 20 min. Because this method is portable, rapid, and easy to operate, it has great potential for point-of-care testing. Additionally, through multiple device networking, a real-time artificial intelligence monitoring system for pathogens was developed on a cloud server. Through data reception, analysis, and visualization, the system can send early warning signals for disease control and prevention. Thus, anti-epidemic measures can be implemented effectively, and deploying and running this system can improve the capabilities for the prevention and control of infectious diseases.
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Affiliation(s)
- Yu Fu
- Molecular Diagnosis and Treatment Center for Infectious DiseasesDermatology HospitalSouthern Medical UniversityGuangzhouChina
- Longgang District Central Hospital of ShenzhenShenzhenChina
- National Clinical Research Center for Infectious Diseasethe Second Affiliated Hospital of Southern University of Science and TechnologyShenzhen Third People's HospitalShenzhenChina
| | - Yan Liu
- Institute for Health Innovation and TechnologyNational University of SingaporeSingaporeSingapore
| | - Wenlu Song
- Molecular Diagnosis and Treatment Center for Infectious DiseasesDermatology HospitalSouthern Medical UniversityGuangzhouChina
| | - Delong Yang
- Department of Burn Surgerythe First People's Hospital of FoshanFoshanChina
| | - Wenjie Wu
- Department of Burn and Plastic SurgeryGuangzhou First People's HospitalSouth China University of TechnologyGuangzhouChina
| | - Jingyan Lin
- National Clinical Research Center for Infectious Diseasethe Second Affiliated Hospital of Southern University of Science and TechnologyShenzhen Third People's HospitalShenzhenChina
| | - Xiongtiao Yang
- Longgang District Central Hospital of ShenzhenShenzhenChina
| | - Jian Zeng
- Longgang District Central Hospital of ShenzhenShenzhenChina
| | - Lingzhi Rong
- Longgang District Central Hospital of ShenzhenShenzhenChina
| | - Jiaojiao Xia
- Longgang District Central Hospital of ShenzhenShenzhenChina
| | - Hongyi Lei
- Longgang District Central Hospital of ShenzhenShenzhenChina
| | - Ronghua Yang
- Department of Burn and Plastic SurgeryGuangzhou First People's HospitalSouth China University of TechnologyGuangzhouChina
| | - Mingxia Zhang
- National Clinical Research Center for Infectious Diseasethe Second Affiliated Hospital of Southern University of Science and TechnologyShenzhen Third People's HospitalShenzhenChina
| | - Yuhui Liao
- Molecular Diagnosis and Treatment Center for Infectious DiseasesDermatology HospitalSouthern Medical UniversityGuangzhouChina
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8
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Kumar M, Joshi M, Jiang G, Yamada R, Honda R, Srivastava V, Mahlknecht J, Barcelo D, Chidambram S, Khursheed A, Graham DW, Goswami R, Kuroda K, Tiwari A, Joshi C. Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 337:122471. [PMID: 37652227 DOI: 10.1016/j.envpol.2023.122471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 07/30/2023] [Accepted: 08/26/2023] [Indexed: 09/02/2023]
Abstract
In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.
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Affiliation(s)
- Manish Kumar
- Sustainability Cluster, School of Advanced Engineering, UPES, Dehradun, Uttarakhand, 248007, India; Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey, 64849, Nuevo Leon, Mexico.
| | - Madhvi Joshi
- Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat, 248007, India
| | - Guangming Jiang
- School of Civil, Mining, Environmental and Architectural Engineering, University of Wollongong, Australia
| | - Rintaro Yamada
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, 920-1192, Japan; Yachiyo Engineering Co., Ltd. Tokyo, 111-8648, Japan
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, 920-1192, Japan
| | - Vaibhav Srivastava
- Department of Botany, Faculty of Science, University of Allahabad, Prayagraj, 211002, India
| | - Jürgen Mahlknecht
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey, 64849, Nuevo Leon, Mexico
| | - Damia Barcelo
- Sustainability Cluster, School of Advanced Engineering, UPES, Dehradun, Uttarakhand, 248007, India; 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 Tecnol'ogic de la Universitat de Girona, c/Emili Grahit, 101, Edifici H2O, 17003, Girona, Spain
| | | | - Anwar Khursheed
- Department of Civil Engineering, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia
| | - David W Graham
- Department of Civil and Environmental Engineering, Newcastle University, Newcastle, UK
| | - Ritusmita Goswami
- Centre for Ecology, Environment and Sustainable Development, Tata Institute of Social Sciences, Guwahati, India
| | - Keisuke Kuroda
- Department of Environmental and Civil Engineering, Toyama Prefectural University, 5180 Kurokawa, Imizu, 939-0398, Japan
| | - Ananda Tiwari
- Expert Microbiology Unit, Finnish Institute for Health and Welfare, 70701 Kuopio, Finland
| | - Chaitanya Joshi
- Gujarat Biotechnology Research Centre, Gandhinagar, Gujarat, 248007, India
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9
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Ruan Y, Huang T, Zhou W, Zhu J, Liang Q, Zhong L, Tang X, Liu L, Chen S, Xie Y. The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19. Sci Rep 2023; 13:14705. [PMID: 37679512 PMCID: PMC10484897 DOI: 10.1038/s41598-023-41939-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 09/04/2023] [Indexed: 09/09/2023] Open
Abstract
Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Index (BSI) of seven search terms from 1 January to 30 April, 2022 in 12 provinces/prefectures to explore the variation in China. Two search peaks of "COVID-19 epidemic", "Novel Coronavirus" and "COVID-19" can be observed. One in January, which showed 3 days lead time in Henan and Tianjin. Another on early March, which occurred 0-28 days ahead of the local epidemic but the lead time had spatial variation. It was 4 weeks in Shanghai, 2 weeks in Henan and 5-8 days in Jilin Province, Jilin and Changchun Prefecture. But it was only 1-3 days in Tianjin, Quanzhou Prefecture, Fujian Province and 0 day in Shenzhen, Shandong Province, Qingdao and Yanbian Prefecture. The BSI was high correlated (rs:0.70-0.93) to the number of cases with consistent epidemiological change trend. The lead time of BSI had spatial and temporal variation and was close related to the strength of nucleic acid testing. The case detection ability should be strengthened when perceiving BSI increase.
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Affiliation(s)
- Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Tengda Huang
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Wanwan Zhou
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Jinhui Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Qiuyu Liang
- Department of Health Management, The People's Hospital of Guangxi Zhuang Autonomous Region & Research Center of Health Management, Guangxi Academy of Medical Sciences, Nanning, China
| | - Lixian Zhong
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Xiaofen Tang
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Lu Liu
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Shiwen Chen
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China
| | - Yihong Xie
- Department of Epidemiology and Biostatistics, Guangxi Medical University, Nanning, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, China.
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10
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Rabe A, Ravuri S, Burnor E, Steele JA, Kantor RS, Choi S, Forman S, Batjiaka R, Jain S, León TM, Vugia DJ, Yu AT. Correlation between wastewater and COVID-19 case incidence rates in major California sewersheds across three variant periods. JOURNAL OF WATER AND HEALTH 2023; 21:1303-1317. [PMID: 37756197 PMCID: wh_2023_173 DOI: 10.2166/wh.2023.173] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Monitoring for COVID-19 through wastewater has been used for adjunctive public health surveillance, with SARS-CoV-2 viral concentrations in wastewater correlating with incident cases in the same sewershed. However, the generalizability of these findings across sewersheds, laboratory methods, and time periods with changing variants and underlying population immunity has not been well described. The California Department of Public Health partnered with six wastewater treatment plants starting in January 2021 to monitor wastewater for SARS-CoV-2, with analyses performed at four laboratories. Using reported PCR-confirmed COVID-19 cases within each sewershed, the relationship between case incidence rates and wastewater concentrations collected over 14 months was evaluated using Spearman's correlation and linear regression. Strong correlations were observed when wastewater concentrations and incidence rates were averaged (10- and 7-day moving window for wastewater and cases, respectively, ρ = 0.73-0.98 for N1 gene target). Correlations remained strong across three time periods with distinct circulating variants and vaccination rates (winter 2020-2021/Alpha, summer 2021/Delta, and winter 2021-2022/Omicron). Linear regression revealed that slopes of associations varied by the dominant variant of concern, sewershed, and laboratory (β = 0.45-1.94). These findings support wastewater surveillance as an adjunctive public health tool to monitor SARS-CoV-2 community trends.
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Affiliation(s)
- Angela Rabe
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA; These first authors contributed equally to this manuscript. E-mail:
| | - Sindhu Ravuri
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA; These first authors contributed equally to this manuscript
| | - Elisabeth Burnor
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA
| | - Joshua A Steele
- Southern California Coastal Water Research Project (SCCWRP), Department of Microbiology, Costa Mesa, CA, USA
| | - Rose S Kantor
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
| | - Samuel Choi
- Orange County Sanitation District, Fountain Valley, CA, USA
| | - Stanislav Forman
- Zymo Research Corp. Department of Sample Collection and Nucleic Acid Purification, Zymo Research Corp., Irvine, CA, USA
| | - Ryan Batjiaka
- San Francisco Public Utilities Commission, San Francisco, CA, USA
| | - Seema Jain
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA
| | - Tomás M León
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA
| | - Duc J Vugia
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA
| | - Alexander T Yu
- California Department of Public Health COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond and Sacramento, CA, USA
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11
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Ciannella S, González-Fernández C, Gomez-Pastora J. Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 878:162953. [PMID: 36948304 PMCID: PMC10028212 DOI: 10.1016/j.scitotenv.2023.162953] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 05/13/2023]
Abstract
On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.
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Affiliation(s)
- Stefano Ciannella
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA.
| | - Cristina González-Fernández
- Department of Chemical Engineering, Texas Tech University, Lubbock 79409, TX, USA; Departamento de Ingenierías Química y Biomolecular, Universidad de Cantabria, Avda. Los Castros, s/n, 39005 Santander, Spain.
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12
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Trigo-Tasende N, Vallejo JA, Rumbo-Feal S, Conde-Pérez K, Vaamonde M, López-Oriona Á, Barbeito I, Nasser-Ali M, Reif R, Rodiño-Janeiro BK, Fernández-Álvarez E, Iglesias-Corrás I, Freire B, Tarrío-Saavedra J, Tomás L, Gallego-García P, Posada D, Bou G, López-de-Ullibarri I, Cao R, Ladra S, Poza M. Wastewater early warning system for SARS-CoV-2 outbreaks and variants in a Coruña, Spain. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27877-3. [PMID: 37286834 DOI: 10.1007/s11356-023-27877-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023]
Abstract
Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8-36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.
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Affiliation(s)
- Noelia Trigo-Tasende
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Juan A Vallejo
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Soraya Rumbo-Feal
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Kelly Conde-Pérez
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Manuel Vaamonde
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ángel López-Oriona
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Inés Barbeito
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Mohammed Nasser-Ali
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Rubén Reif
- Center for Research in Biological Chemistry and Molecular Materials (CiQUS), University of Santiago de Compostela (USC), 15782, Santiago de Compostela, Spain
| | - Bruno K Rodiño-Janeiro
- BFlow, University of Santiago de Compostela (USC) and Health Research Institute of Santiago de Compostela (IDIS), Campus Vida, 15706, Santiago de Compostela, A Coruña, Spain
| | - Elisa Fernández-Álvarez
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Iago Iglesias-Corrás
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Borja Freire
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Javier Tarrío-Saavedra
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Laura Tomás
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - Pilar Gallego-García
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
| | - David Posada
- CINBIO, Universidade de Vigo, 36310, Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36312, Vigo, Spain
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, 36310, Vigo, Spain
| | - Germán Bou
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain
| | - Ignacio López-de-Ullibarri
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Ricardo Cao
- Research Group MODES, Research Center for Information and Communication Technologies (CITIC), University of A Coruña (UDC), Campus de Elviña, 15071 , A Coruña, Spain
| | - Susana Ladra
- University of A Coruña (UDC), Research Center for Information and Communication Technologies (CITIC), Database Laboratory, Campus de Elviña, 15071, A Coruña, Spain
| | - Margarita Poza
- University of A Coruña (UDC) - Microbiome and Health group (meiGAbiome), Institute of Biomedical Research (INIBIC) - University Hospital of A Coruña (CHUAC) - Interdisciplinary Center for Chemistry and Biology (CICA) - Spanish Network for Infectious Diseases (CIBERINFEC-ISCIII), Campus da Zapateira, 15008, A Coruña, Spain.
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13
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Khan M, Li L, Haak L, Payen SH, Carine M, Adhikari K, Uppal T, Hartley PD, Vasquez-Gross H, Petereit J, Verma SC, Pagilla K. Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation. One Health 2023; 16:100536. [PMID: 37041760 PMCID: PMC10074727 DOI: 10.1016/j.onehlt.2023.100536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/13/2023] Open
Abstract
Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.
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Affiliation(s)
- Majid Khan
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Lin Li
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Laura Haak
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Shannon Harger Payen
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Madeline Carine
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
| | - Kabita Adhikari
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Timsy Uppal
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Paul D. Hartley
- Nevada Genomics Center, University of Nevada, Reno, NV 89557, USA
| | - Hans Vasquez-Gross
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Juli Petereit
- Nevada Bioinformatics Center (RRID:SCR_017802), University of Nevada, Reno, NV 89557, USA
| | - Subhash C. Verma
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV 89557, USA
| | - Krishna Pagilla
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV 89557, USA
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14
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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: 10] [Impact Index Per Article: 10.0] [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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15
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Brooks YM, Gryskwicz B, Sidaway E, Shelley B, Coroi L, Downing M, Downing T, McDonnell S, Ostrye D, Hoop K, Parrish G. A case study of a community-organized wastewater surveillance in a small community: correlating weekly reported COVID-19 cases with SARS-CoV-2 RNA concentrations during fall 2020 to summer 2021 in Yarmouth, ME. JOURNAL OF WATER AND HEALTH 2023; 21:329-342. [PMID: 37338313 PMCID: wh_2023_238 DOI: 10.2166/wh.2023.238] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Wastewater surveillance offers a rapid evaluation of SARS-CoV-2 transmission in a community. We describe how a community group, the Yarmouth Wastewater Testing Team (YWTT), in Yarmouth, Maine, (population 8,990) utilized an asset-based community design framework to organize and manage a program to monitor SARS-CoV-2 RNA concentrations. From September 22, 2020 through June 8, 2021, the YWTT disseminated weekly reports of the wastewater results and reported COVID-19 cases within the Yarmouth postal code. After high and increasing SARS-CoV-2 RNA concentrations, the YWTT issued two community advisories to encourage extra care to reduce exposure. Correlations between SARS-CoV-2 RNA concentrations and COVID-19 cases were stronger the week after sampling, and the average of the COVID-19 cases during the week of sampling and the following week, indicating that surveillance provided advance notice of cases. A 10% increase in SARS-CoV-2 RNA concentrations was associated with a 13.29% increase in the average number of weekly reported cases of COVID-19 during the week of sampling and the following week (R2 = 0.42; p < 0.001). Adjusting for viral recovery (December 21, 2020 through June 8, 2021), improved R2 from 0.60 to 0.68. Wastewater surveillance was an effective tool for the YWTT to quickly respond to viral transmission.
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Affiliation(s)
- Yolanda M Brooks
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Bailey Gryskwicz
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Eilidh Sidaway
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Brianna Shelley
- Department of Sciences, St. Joseph's College of Maine, 278 White's Bridge Rd, Standish, ME 04084, USA E-mail: ;
| | - Laura Coroi
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Margaret Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Tom Downing
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Sharon McDonnell
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Dan Ostrye
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
| | - Katrina Hoop
- Department of Social Sciences, University of Maine at Augusta, 46 University Drive, Augusta, ME 04330, USA
| | - Gib Parrish
- Wastewater Testing Team, Yarmouth Community Coronavirus Task Force, C/O Yarmouth Town Hall, 200 Main St., Yarmouth, ME 04096, USA
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16
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Li Q, Lee BE, Gao T, Qiu Y, Ellehoj E, Yu J, Diggle M, Tipples G, Maal-Bared R, Hinshaw D, Sikora C, Ashbolt NJ, Talbot J, Hrudey SE, Pang X. Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment. J Environ Sci (China) 2023; 125:843-850. [PMID: 36375966 PMCID: PMC9068596 DOI: 10.1016/j.jes.2022.04.047] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/24/2022] [Accepted: 04/27/2022] [Indexed: 05/03/2023]
Abstract
With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control.
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Affiliation(s)
- Qiaozhi Li
- School of Public Health, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Bonita E Lee
- Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Erik Ellehoj
- University of Alberta Central Receiving, Edmonton, Alberta, T6G 2R3, Canada
| | - Jiaao Yu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Mathew Diggle
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | - Graham Tipples
- Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
| | | | - Deena Hinshaw
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Christopher Sikora
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Nicholas J Ashbolt
- Faculty of Science and Engineering, Southern Cross University, East Lismore NSW 2480, Australia
| | - James Talbot
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada.
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17
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Dhasarathan C, Hasan MK, Islam S, Abdullah S, Mokhtar UA, Javed AR, Goundar S. COVID-19 health data analysis and personal data preserving: A homomorphic privacy enforcement approach. COMPUTER COMMUNICATIONS 2023; 199:87-97. [PMID: 36531214 PMCID: PMC9747234 DOI: 10.1016/j.comcom.2022.12.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/13/2022] [Accepted: 12/01/2022] [Indexed: 05/14/2023]
Abstract
COVID-19 data analysis and prediction from patient data repository collected from hospitals and health organizations. Users' credentials and personal information are at risk; it could be an unrecoverable issue worldwide. A Homomorphic identification of possible breaches could be more appropriate for minimizing the risk factors in preventing personal data. Individual user privacy preservation is a must-needed research focus in various fields. Health data generated and collected information from multiple scenarios increasing the complexity involved in maintaining secret patient information. A homomorphic-based systematic approach with a deep learning process could reduce depicts and illegal functionality of unknown organizations trying to have relation to the environment and physical and social relations. This article addresses the homomorphic standard system functionality, which refers to all the functional aspects of deep learning system requirements in COVID-19 health management. Moreover, this paper spotlights the metric privacy incorporation for improving the Deep Learning System (DPLS) approaches for solving the healthcare system's complex issues. It is absorbed from the result analysis Homomorphic-based privacy observation metric gradually improves the effectiveness of the deep learning process in COVID-19-health care management.
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Affiliation(s)
- Chandramohan Dhasarathan
- Thapar Institute of Engineering & Technology, ECED, Department of Computer Science & Engineering, Punjab, India
| | - Mohammad Kamrul Hasan
- Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia
| | - Shayla Islam
- Institute of Computer Science and Digital Innovation, UCSI University, Malaysia
| | - Salwani Abdullah
- Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia
| | - Umi Asma Mokhtar
- Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, Malaysia
| | - Abdul Rehman Javed
- Department of Cyber Security, Air University, Islamabad, Pakistan
- Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon
| | - Sam Goundar
- School of Computing and Innovative Technologies, British University Vietnam, Viet Nam
- School of Science, Engineering, and Technology, RMIT University, Viet Nam
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18
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Maal-Bared R, Qiu Y, Li Q, Gao T, Hrudey SE, Bhavanam S, Ruecker NJ, Ellehoj E, Lee BE, Pang X. Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:158964. [PMID: 36167131 PMCID: PMC9508694 DOI: 10.1016/j.scitotenv.2022.158964] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 05/02/2023]
Abstract
Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.
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Affiliation(s)
- Rasha Maal-Bared
- Quality Assurance and Environment, EPCOR Water, Edmonton, Alberta, Canada.
| | - Yuanyuan Qiu
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Qiaozhi Li
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Tiejun Gao
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Steve E Hrudey
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Sudha Bhavanam
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Norma J Ruecker
- Water Quality Services, City of Calgary, Calgary, Alberta, Canada
| | - Erik Ellehoj
- Ellehoj Redmond Consulting, Edmonton, Alberta, Canada
| | - Bonita E Lee
- Department of Paediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Xiaoli Pang
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada; Public Health Laboratories (ProvLab), Alberta Precision Laboratories (APL), Edmonton, Alberta, Canada
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19
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Mahlangeni N, Street R, Horn S, Mathee A, Mangwana N, Dias S, Sharma JR, Ramharack P, Louw J, Reddy T, Surujlal-Naicker S, Nkambule S, Webster C, Mdhluli M, Gray G, Muller C, Johnson R. Using Wastewater Surveillance to Compare COVID-19 Outbreaks during the Easter Holidays over a 2-Year Period in Cape Town, South Africa. Viruses 2023; 15:162. [PMID: 36680203 PMCID: PMC9863979 DOI: 10.3390/v15010162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 12/22/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open
Abstract
Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown to be an important approach to determine early outbreaks of infections. Wastewater-based epidemiology (WBE) is regarded as a complementary tool for monitoring SARS-CoV-2 trends in communities. In this study, the changes in the SARS-CoV-2 RNA levels in wastewater during Easter holidays in 2021 and 2022 in the City of Cape Town were monitored over nine weeks. Our findings showed a statistically significant difference in the SARS-CoV-2 RNA viral load between the study weeks over the Easter period in 2021 and 2022, except for study week 1 and 4. During the Easter week, 52% of the wastewater treatment plants moved from the lower (low viral RNA) category in 2021 to the higher (medium to very high viral RNA) categories in 2022. As a result, the median SARS-CoV-2 viral loads where higher during the Easter week in 2022 than Easter week in 2021 (p = 0.0052). Mixed-effects model showed an association between the SARS-CoV-2 RNA viral loads and Easter week over the Easter period in 2021 only (p < 0.01). The study highlights the potential of WBE to track outbreaks during the holiday period.
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Affiliation(s)
- Nomfundo Mahlangeni
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Renée Street
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
- Environmental Health Department, Faculty of Health Sciences, University of Johannesburg, Johannesburg 2028, South Africa
| | - Suranie Horn
- Occupational Hygiene and Health Research Initiative, North-West University, Potchefstroom 2531, South Africa
| | - Angela Mathee
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
- Environmental Health Department, Faculty of Health Sciences, University of Johannesburg, Johannesburg 2028, South Africa
| | - Noluxabiso Mangwana
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Stephanie Dias
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Jyoti Rajan Sharma
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
| | - Pritika Ramharack
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Johan Louw
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa
| | - Tarylee Reddy
- Biostatistics Research Unit, South African Medical Research Council (SAMRC), Durban 4091, South Africa
| | - Swastika Surujlal-Naicker
- Scientific Services, Water and Sanitation Department, City of Cape Town Metropolitan Municipality, Cape Town 8000, South Africa
| | - Sizwe Nkambule
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Candice Webster
- Environment & Health Research Unit, South African Medical Research Council (SAMRC), Johannesburg 2028, South Africa
| | - Mongezi Mdhluli
- Chief Research Operations Office, South African Medical Research Council (SAMRC), Tygerberg 7050, South Africa
| | - Glenda Gray
- Office of the President, South African Medical Research Council (SAMRC), Tygerberg 7050, South Africa
| | - Christo Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardio-Metabolic Research in Africa, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Rabia Johnson
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg 7505, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, Centre for Cardio-Metabolic Research in Africa, Stellenbosch University, Stellenbosch 7600, South Africa
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20
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Zahmatkesh S, Rezakhani Y, Chofreh AG, Karimian M, Wang C, Ghodrati I, Hasan M, Sillanpaa M, Panchal H, Khan R. SARS-CoV-2 removal by mix matrix membrane: A novel application of artificial neural network based simulation in MATLAB for evaluating wastewater reuse risks. CHEMOSPHERE 2023; 310:136837. [PMID: 36252897 PMCID: PMC9560862 DOI: 10.1016/j.chemosphere.2022.136837] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/20/2022] [Accepted: 10/07/2022] [Indexed: 05/09/2023]
Abstract
The COVID-19 outbreak led to the discovery of SARS-CoV-2 in sewage; thus, wastewater treatment plants (WWTPs) could have the virus in their effluent. However, whether SARS-CoV-2 is eradicated by sewage treatment is virtually unknown. Specifically, the objectives of this study include (i) determining whether a mixed matrixed membrane (MMM) is able to remove SARS-CoV-2 (polycarbonate (PC)-hydrous manganese oxide (HMO) and PC-silver nanoparticles (Ag-NP)), (ii) comparing filtration performance among different secondary treatment processes, and (iii) evaluating whether artificial neural networks (ANNs) can be employed as performance indicators to reduce SARS-CoV-2 in the treatment of sewage. At Shariati Hospital in Mashhad, Iran, secondary treatment effluent during the outbreak of COVID-19 was collected from a WWTP. There were two PC-Ag-NP and PC-HMO processes at the WWTP targeted. RT-qPCR was employed to detect the presence of SARS-CoV-2 in sewage fractions. For the purposes of determining SARS-CoV-2 prevalence rates in the treated effluent, 10 L of effluent specimens were collected in middle-risk and low-risk treatment MMMs. For PC-HMO, the log reduction value (LRV) for SARS-CoV-2 was 1.3-1 log10 for moderate risk and 0.96-1 log10 for low risk, whereas for PC-Ag-NP, the LRV was 0.99-1.3 log10 for moderate risk and 0.94-0.98 log10 for low risk. MMMs demonstrated the most robust absorption performance during the sampling period, with the least significant LRV recorded in PC-Ag-NP and PC-HMO at 0.94 log10 and 0.96 log10, respectively.
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Affiliation(s)
- Sasan Zahmatkesh
- Department of Chemical Engineering, University of Science and Technology of Mazandaran, P.O. Box 48518-78195, Behshahr, Iran; Tecnologico de Monterrey, Escuela de Ingenieríay Ciencias, Puebla, Mexico.
| | - Yousof Rezakhani
- Department of Civil Engineering, Pardis Branch, Islamic Azad University, Pardis, Iran
| | - Abdoulmohammad Gholamzadeh Chofreh
- Sustainable Process Integration Laboratory, SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology, VUT Brno, Technická 2896/2, 616 00, Brno, Czech Republic
| | - Melika Karimian
- Faculty of Civil Engineering, Architecture and Urban Planning, University of Eyvanekey, Iran
| | - Chongqing Wang
- School of Chemical Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Iman Ghodrati
- Department of Computer Engineering, Bojnourd Branch, Islamic Azad University, Bojnourd, Iran
| | - Mudassir Hasan
- Department of Chemical Engineering, College of Engineering, King Khalid University, Abha, 61411, Saudi Arabia
| | - Mika Sillanpaa
- Faculty of Science and Technology, School of Applied Physics, University Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia; International Research Centre of Nanotechnology for Himalayan Sustainability (IRCNHS), Shoolini University, Solan, 173212, Himachal Pradesh, India; Department of Chemical Engineering, School of Mining, Metallurgy and Chemical Engineering, University of Johannesburg, P. O. Box 17011, Doornfontein, 2028, South Africa
| | - Hitesh Panchal
- Mechanical Engineering Department, Government Engineering College, Patan, Gujarat, India
| | - Ramsha Khan
- Faculty of Civil Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Barabanki, 225003, UP, India
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21
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Farkas K, Williams R, Alex-Sanders N, Grimsley JMS, Pântea I, Wade MJ, Woodhall N, Jones DL. Wastewater-based monitoring of SARS-CoV-2 at UK airports and its potential role in international public health surveillance. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001346. [PMID: 36963000 PMCID: PMC10021541 DOI: 10.1371/journal.pgph.0001346] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/24/2022] [Indexed: 01/20/2023]
Abstract
It is well established that air travel plays a key role in the global spread of many enteric and respiratory diseases, including COVID-19. Even with travel restrictions (e.g. mask wearing, negative COVID-19 test prior to departure), SARS-CoV-2 may be transmitted by asymptomatic or pre-symptomatic individuals carrying the virus. Due to the limitation of current clinical surveillance approaches, complementary methods need to be developed to allow estimation of the frequency of SARS-CoV-2 entry across international borders. Wastewater-based epidemiology (WBE) represents one such approach, allowing the unbiased sampling of SARS-CoV-2 carriage by passenger cohorts entering via airports. In this study, we monitored sewage in samples from terminals (n = 150) and aircraft (n = 32) at three major international airports in the UK for 1-3 weeks in March 2022. As the raw samples were more turbid than typical municipal wastewater, we used beef extract treatment followed by polyethylene glycol (PEG) precipitation to concentrate viruses, followed by reverse transcription quantitative PCR (RT-qPCR) for the detection of SARS-CoV-2 and a faecal indicator virus, crAssphage. All samples taken from sewers at the arrival terminals of Heathrow and Bristol airports, and 85% of samples taken from sites at Edinburgh airport, were positive for SARS-CoV-2. This suggests a high COVID-19 prevalence among passengers and/or airport staff members. Samples derived from aircraft also showed 93% SARS-CoV-2 positivity. No difference in viral prevalence was found before and after COVID-19 travel restrictions were lifted. Our results suggest that WBE is a useful tool for monitoring the global transfer rate of human pathogens and other disease-causing agents across international borders and should form part of wider international efforts to monitor and contain the spread of future disease outbreaks.
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Affiliation(s)
- Kata Farkas
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey, United Kingdom
| | - Rachel Williams
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Natasha Alex-Sanders
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Jasmine M S Grimsley
- Data, Analytics, and Surveillance Group, UK Health Security Agency, London, United Kingdom
- The London Data Company, London, United Kingdom
| | - Igor Pântea
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Matthew J Wade
- Data, Analytics, and Surveillance Group, UK Health Security Agency, London, United Kingdom
- School of Engineering, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Nick Woodhall
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Davey L Jones
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- Food Futures Institute, Murdoch University, Murdoch, Australia
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22
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Smith T, Holm RH, Keith RJ, Amraotkar AR, Alvarado CR, Banecki K, Choi B, Santisteban IC, Bushau-Sprinkle AM, Kitterman KT, Fuqua J, Hamorsky KT, Palmer KE, Brick JM, Rempala GA, Bhatnagar A. Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158567. [PMID: 36084773 PMCID: PMC9444845 DOI: 10.1016/j.scitotenv.2022.158567] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/07/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.
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Affiliation(s)
- Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Rachel J Keith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Alok R Amraotkar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Chance R Alvarado
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
| | - Krzysztof Banecki
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Boseung Choi
- Division of Big Data Science, Korea University, Sejong, South Korea; Biomedical Mathematics Group, Institute for Basic Science, Daejeon, South Korea
| | - Ian C Santisteban
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA
| | - Adrienne M Bushau-Sprinkle
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Kathleen T Kitterman
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA
| | - Joshua Fuqua
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Pharmacology and Toxicology, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Krystal T Hamorsky
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | - Kenneth E Palmer
- Center for Predictive Medicine for Biodefense and Emerging Infectious Diseases, University of Louisville, Louisville, KY 40202, USA; Department of Pharmacology and Toxicology, School of Medicine, University of Louisville, Louisville, KY 40202, USA
| | | | - Grzegorz A Rempala
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH 43210, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY 40202, USA.
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23
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Evaluation of viral concentration and extraction methods for SARS-CoV-2 recovery from wastewater using droplet digital and quantitative RT-PCR. CASE STUDIES IN CHEMICAL AND ENVIRONMENTAL ENGINEERING 2022; 6:100224. [PMID: 37520924 PMCID: PMC9222221 DOI: 10.1016/j.cscee.2022.100224] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/17/2022] [Accepted: 06/21/2022] [Indexed: 05/19/2023]
Abstract
The ongoing pandemic caused by the emergence of SARS-CoV-2 has resulted in millions of deaths worldwide despite the various measures announced by the authorities. Wastewater-based epidemiology has the ability to provide a day-to-day estimation of the number of infected people in a fast and cost-effective manner. However, owing to the complex nature of wastewater, wastewater monitoring for viral genome copies is affected by the extensive viral fragmentation that takes place all the way to the sewage and the analytical lab. The aim of this study was to evaluate different methodologies for the concentration and extraction of viruses in wastewaters and to select and improve an option that maximizes the recovery of SARS-CoV-2. We compare 5 different concentration methods and 4 commercially available kits for the RNA extraction. To evaluate the performance and the recovery of these, SARS-CoV-2 isolated from patients was used as a spike control. Additionally, the presence of SARS-CoV-2 in all wastewater samples was determined using reverse transcription quantitative PCR (RT-qPCR) and reverse transcription droplet digital PCR (RT-ddPCR), targeting three genetic markers (N1, N2 and N3). Using spiked samples, recoveries were estimated 2.1–37.6% using different extraction kits and 0.1–2.1% using different concentration kits. It was found that a direct capture-based method, evaluated against a variety of concentration methods, is the best in terms of recovery, time and cost. Interestingly, we noticed a good agreement between the results provided by RT-qPCR and RT-ddPCR in terms of recovery. This evaluation can serve as a guide for laboratories establishing a protocol to perform wastewater monitoring of SARS-CoV-2. Overall, data presented here reinforces the validity of WBE for SARS-CoV-2 surveillance, uncovers potential caveats in the selection of concentration and extraction protocols and points towards optimal solutions to maximize its potential.
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24
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Sridhar J, Parit R, Boopalakrishnan G, Rexliene MJ, Praveen R, Viswananathan B. Importance of wastewater-based epidemiology for detecting and monitoring SARS-CoV-2. CASE STUDIES IN CHEMICAL AND ENVIRONMENTAL ENGINEERING 2022; 6:100241. [PMID: 37520919 PMCID: PMC9341170 DOI: 10.1016/j.cscee.2022.100241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 08/01/2023]
Abstract
Coronavirus disease caused by the SARS-CoV-2 virus has emerged as a global challenge in terms of health and disease monitoring. COVID-19 infection is mainly spread through the SARS-CoV-2 infection leading to the development of mild to severe clinical manifestations. The virus binds to its cognate receptor ACE2 which is widely expressed among different tissues in the body. Notably, SARS-CoV-2 shedding in the fecal samples has been reported through the screening of sewage water across various countries. Wastewater screening for the presence of SARS-CoV-2 provides an alternative method to monitor infection threat, variant identification, and clinical evaluation to restrict the virus progression. Multiple cohort studies have reported the application of wastewater treatment approaches and epidemiological significance in terms of virus monitoring. Thus, the manuscript outlines consolidated and systematic information regarding the application of wastewater-based epidemiology in terms of monitoring and managing a viral disease outbreak like COVID-19.
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Affiliation(s)
- Jayavel Sridhar
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Rahul Parit
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | | | - M Johni Rexliene
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Rajkumar Praveen
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
| | - Balaji Viswananathan
- Department of Biotechnology (DDE), Madurai Kamaraj University, Madurai, 625021, Tamilnadu, India
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25
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Pang X, Gao T, Ellehoj E, Li Q, Qiu Y, Maal-Bared R, Sikora C, Tipples G, Diggle M, Hinshaw D, Ashbolt NJ, Talbot J, Hrudey SE, Lee BE. Wastewater-Based Surveillance Is an Effective Tool for Trending COVID-19 Prevalence in Communities: A Study of 10 Major Communities for 17 Months in Alberta. ACS ES&T WATER 2022; 2:2243-2254. [PMID: 36380772 PMCID: PMC9514327 DOI: 10.1021/acsestwater.2c00143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 06/16/2023]
Abstract
The correlations between SARS-CoV-2 RNA levels in wastewater from 12 wastewater treatment plants and new COVID-19 cases in the corresponding sewersheds of 10 communities were studied over 17 months. The analysis from the longest continuous surveillance reported to date revealed that SARS-CoV-2 RNA levels correlated well with temporal changes of COVID-19 cases in each community. The strongest correlation was found during the third wave (r = 0.97) based on the population-weighted SARS-CoV-2 RNA levels in wastewater. Different correlations were observed (r from 0.51 to 0.86) in various sizes of communities. The population in the sewershed had no observed effects on the strength of the correlation. Fluctuation of SARS-CoV-2 RNA levels in wastewater mirrored increases and decreases of COVID-19 cases in the corresponding community. Since the viral shedding to sewers from all infected individuals is included, wastewater-based surveillance provides an unbiased and no-discriminate estimation of the prevalence of COVID-19 compared with clinical testing that was subject to testing-seeking behaviors and policy changes. Wastewater-based surveillance on SARS-CoV-2 represents a temporal trend of COVID-19 disease burden and is an effective and supplementary monitoring when the number of COVID-19 cases reaches detectable thresholds of SARS-CoV-2 RNA in wastewater of treatment facilities serving various sizes of populations.
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Affiliation(s)
- Xiaoli Pang
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Tiejun Gao
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Erik Ellehoj
- Ellehoj
Redmond Consulting, Edmonton, Alberta T6G 0Y4, Canada
| | - Qiaozhi Li
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Yuanyuan Qiu
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - Christopher Sikora
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Graham Tipples
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Mathew Diggle
- Alberta
Precision Laboratories, Edmonton, Alberta T6G 2J2, Canada
| | - Deena Hinshaw
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | | | - James Talbot
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Steve E. Hrudey
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
| | - Bonita E. Lee
- Department
of Laboratory Medicine and Pathology, School of Public Health, Department of Medicine, and Department of
Pediatrics, University of Alberta, Edmonton, Alberta T6G 2E2, Canada
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Rainey AL, Loeb JC, Robinson SE, Davis P, Liang S, Lednicky JA, Coker ES, Sabo-Attwood T, Bisesi JH, Maurelli AT. Assessment of a mass balance equation for estimating community-level prevalence of COVID-19 using wastewater-based epidemiology in a mid-sized city. Sci Rep 2022; 12:19085. [PMID: 36352013 PMCID: PMC9645338 DOI: 10.1038/s41598-022-21354-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022] Open
Abstract
Wastewater-based epidemiology (WBE) has emerged as a valuable epidemiologic tool to detect the presence of pathogens and track disease trends within a community. WBE overcomes some limitations of traditional clinical disease surveillance as it uses pooled samples from the entire community, irrespective of health-seeking behaviors and symptomatic status of infected individuals. WBE has the potential to estimate the number of infections within a community by using a mass balance equation, however, it has yet to be assessed for accuracy. We hypothesized that the mass balance equation-based approach using measured SARS-CoV-2 wastewater concentrations can generate accurate prevalence estimates of COVID-19 within a community. This study encompassed wastewater sampling over a 53-week period during the COVID-19 pandemic in Gainesville, Florida, to assess the ability of the mass balance equation to generate accurate COVID-19 prevalence estimates. The SARS-CoV-2 wastewater concentration showed a significant linear association (Parameter estimate = 39.43, P value < 0.0001) with clinically reported COVID-19 cases. Overall, the mass balance equation produced accurate COVID-19 prevalence estimates with a median absolute error of 1.28%, as compared to the clinical reference group. Therefore, the mass balance equation applied to WBE is an effective tool for generating accurate community-level prevalence estimates of COVID-19 to improve community surveillance.
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Affiliation(s)
- Andrew L. Rainey
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA
| | - Julia C. Loeb
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA
| | - Sarah E. Robinson
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Center for Environmental and Human Toxicology, University of Florida, 2187 Mowry Road, PO Box 110885, Gainesville, FL 32611 USA
| | - Paul Davis
- Gainesville Regional Utilities, Gainesville, FL 32614 USA
| | - Song Liang
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA
| | - John A. Lednicky
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA
| | - Eric S. Coker
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA
| | - Tara Sabo-Attwood
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Center for Environmental and Human Toxicology, University of Florida, 2187 Mowry Road, PO Box 110885, Gainesville, FL 32611 USA
| | - Joseph H. Bisesi
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Center for Environmental and Human Toxicology, University of Florida, 2187 Mowry Road, PO Box 110885, Gainesville, FL 32611 USA
| | - Anthony T. Maurelli
- grid.15276.370000 0004 1936 8091Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610 USA ,grid.15276.370000 0004 1936 8091Emerging Pathogens Institute, University of Florida, 2055 Mowry Road, PO Box 100009, Gainesville, FL 32610 USA
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Cutrupi F, Cadonna M, Manara S, Postinghel M, La Rosa G, Suffredini E, Foladori P. The wave of the SARS-CoV-2 Omicron variant resulted in a rapid spike and decline as highlighted by municipal wastewater surveillance. ENVIRONMENTAL TECHNOLOGY & INNOVATION 2022; 28:102667. [PMID: 35615435 PMCID: PMC9122782 DOI: 10.1016/j.eti.2022.102667] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/12/2022] [Accepted: 05/12/2022] [Indexed: 05/10/2023]
Abstract
This paper highlights the extraordinarily rapid spread of SARS-CoV-2 loads in wastewater that during the Omicron wave in December 2021-February 2022, compared with the profiles acquired in 2020-21 with 410 samples from two wastewater treatment plants (Trento+suburbs, 132,500 inhabitants). Monitoring of SARS-CoV-2 in wastewater focused on: (i) 3 samplings/week and analysis, (ii) normalization to calculate genomic units (GU) inh-1 d-1; (iii) calculation of a 7-day moving average to smooth daily fluctuations; (iv) comparison with the 'current active cases'/100,000 inh progressively affected by the mass vaccination. The time profiles of SARS-CoV-2 in wastewater matched the waves of active cases. In February-April 2021, a viral load of 1.0E+07 GU inh-1 d - 1 corresponded to 700 active cases/100,000 inh. In July-September 2021, although the low current active cases, sewage revealed an appreciable SARS-CoV-2 circulation (in this period 2.2E+07 GU inh-1 d-1 corresponded to 90 active cases/100,000 inh). Omicron was not detected in wastewater until mid-December 2021. The Omicron spread caused a 5-6 fold increase of the viral load in two weeks, reaching the highest peak (2.0-2.2E+08 GU inh-1 d-1 and 4500 active cases/100,000 inh) during the pandemic. In this period, wastewater surveillance anticipated epidemiological data by about 6 days. In winter 2021-22, despite the 4-7 times higher viral loads in wastewater, hospitalizations were 4 times lower than in winter 2020-21 due to the vaccination coverage >80%. The Omicron wave demonstrated that SARS-CoV-2 monitoring of wastewater anticipated epidemiological data, confirming its importance in long-term surveillance.
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Affiliation(s)
- Francesca Cutrupi
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
| | - Maria Cadonna
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Serena Manara
- Department of Cellular Computational and Integrative Biology-CIBIO, Via Sommarive 9, 38123 Trento, Italy
| | - Mattia Postinghel
- ADEP, Agenzia per la Depurazione (Wastewater Treatment Agency), Autonomous Province of Trento, via Gilli 3, 38121 Trento, Italy
| | - Giuseppina La Rosa
- Department of Environment and Health, Istituto Superiore di Sanità, Rome, Italy
| | - Elisabetta Suffredini
- Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - Paola Foladori
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy
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28
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Relationship between SARS-CoV-2 in wastewater and clinical data from five wastewater sheds. JOURNAL OF HAZARDOUS MATERIALS ADVANCES 2022; 8:100159. [PMID: 36619827 PMCID: PMC9448702 DOI: 10.1016/j.hazadv.2022.100159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 08/26/2022] [Accepted: 09/02/2022] [Indexed: 01/17/2023]
Abstract
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic starting in 2019 with nearly 500 million confirmed cases as of April 2022. Infection with SARS-CoV-2 is accompanied by shedding of virus in stool, and its presence in wastewater samples has been documented globally. Therefore, monitoring of SARS-CoV-2 in wastewater offers a promising approach to assess the pandemic situation covering pre-symptomatic and asymptomatic cases in areas with limited clinical testing. In this study, the presence of SARS-CoV-2 RNA in wastewater from five wastewater resource recovery facilities (WRRFs), located in two adjacent counties, was investigated and compared with the number of clinical COVID-19 cases during a 2020-2021 outbreak in United States. Statistical correlation analyses of SARS-CoV-2 viral abundance in wastewater and COVID-19 daily vs weekly clinical cases was performed. While a weak correlation on a daily basis was observed, this correlation improved when weekly clinical case data were applied. The viral fecal indicator Pepper Mild Mottle Virus (PMMoV) was furthermore used to assess the effects of normalization and the impact of dilution due to infiltration in the wastewater sheds. Normalization did not improve the correlations with clinical data. However, PMMoV provided important information about infiltration and presence of industrial wastewater discharge in the wastewater sheds. This study showed the utility of WBE to assist in public health responses to COVID-19, emphasizing that routine monitoring of large WRRFs could provide sufficient information for large-scale dynamics.
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29
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Li L, Uppal T, Hartley PD, Gorzalski A, Pandori M, Picker MA, Verma SC, Pagilla K. Detecting SARS-CoV-2 variants in wastewater and their correlation with circulating variants in the communities. Sci Rep 2022; 12:16141. [PMID: 36167869 PMCID: PMC9514676 DOI: 10.1038/s41598-022-20219-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 09/09/2022] [Indexed: 11/09/2022] Open
Abstract
Detection of SARS-CoV-2 viral load in wastewater has been highly informative in estimating the approximate number of infected individuals in the surrounding communities. Recent developments in wastewater monitoring to determine community prevalence of COVID-19 further extends into identifying SARS-CoV-2 variants, including those being monitored for having enhanced transmissibility. We sequenced genomic RNA derived from wastewater to determine the variants of coronaviruses circulating in the communities. Wastewater samples were collected from Truckee Meadows Water Reclamation Facility (TMWRF) from November 2020 to June 2021. SARS-CoV-2 variants resulting from wastewater were compared with the variants detected in infected individuals' clinical specimens (nasal/nasopharyngeal swabs) during the same period and found conclusively in agreement. Therefore, wastewater monitoring for SARS-CoV-2 variants in the community is a feasible strategy as a complementary tool to clinical specimen testing in the latter's absence.
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Affiliation(s)
- Lin Li
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV, 89557, USA
| | - Timsy Uppal
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV, 89557, USA
| | - Paul D Hartley
- Nevada Genomics Center, University of Nevada, Reno, NV, 89557, USA
| | | | - Mark Pandori
- Nevada State Public Health Laboratory, Reno, NV, USA
- Department of Pathology and Laboratory Medicine, University of Nevada, Reno School of Medicine, Reno, NV, USA
| | - Michael A Picker
- Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas, NV, USA
| | - Subhash C Verma
- Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine, MS320, Reno, NV, 89557, USA.
| | - Krishna Pagilla
- Department of Civil and Environmental Engineering, University of Nevada, MS258, Reno, NV, 89557, USA.
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de Sousa ARV, do Carmo Silva L, de Curcio JS, da Silva HD, Eduardo Anunciação C, Maria Salem Izacc S, Neto FOS, de Paula Silveira Lacerda E. "pySewage": a hybrid approach to predict the number of SARS-CoV-2-infected people from wastewater in Brazil. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:67260-67269. [PMID: 35524091 PMCID: PMC9075719 DOI: 10.1007/s11356-022-20609-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/30/2022] [Indexed: 05/21/2023]
Abstract
It is well known that the new coronavirus pandemic has global environmental, public health, and economic implications. In this sense, this study aims to monitor SARS-CoV-2 in the largest wastewater treatment plant of Goiânia, which processes wastewater from more than 700,000 inhabitants, and to correlate the molecular and clinical data collected. Influent and effluent samples were collected at Dr. Helio de Seixo Britto's wastewater treatment plant from January to August 2021. Viral concentration was performed with polyethylene glycol before viral RNA extraction. Real-time qPCR (N1 and N2 gene assays) was performed to detect and quantify the viral RNA present in the samples. The results showed that 43.63% of the samples were positive. There is no significant difference between the detection of primers N1 (mean 3.23 log10 genome copies/L, std 0.23) and N2 (mean 2.95 log10 genome copies/L, std 0.29); also, there is no significant difference between the detection of influent and effluent samples. Our molecular data revealed a positive correlation with clinical data, and infection prevalence was higher than clinical data. In addition, we developed a user-friendly web application to predict the number of infected people based on the detection of viral load present in wastewater samples and may be applied as a public policy strategy for monitoring ongoing outbreaks.
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Affiliation(s)
| | - Lívia do Carmo Silva
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Juliana Santana de Curcio
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Hugo Delleon da Silva
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
- Universitary Center of Goiás (UNIGOIÁS), Goiânia, Goiás, Brazil
| | - Carlos Eduardo Anunciação
- Department of Biochemistry and Molecular Biology, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
| | - Silvia Maria Salem Izacc
- Department of Genetics, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
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Farkas K, Pellett C, Alex-Sanders N, Bridgman MTP, Corbishley A, Grimsley JMS, Kasprzyk-Hordern B, Kevill JL, Pântea I, Richardson-O’Neill IS, Lambert-Slosarska K, Woodhall N, Jones DL. Comparative Assessment of Filtration- and Precipitation-Based Methods for the Concentration of SARS-CoV-2 and Other Viruses from Wastewater. Microbiol Spectr 2022; 10:e0110222. [PMID: 35950856 PMCID: PMC9430619 DOI: 10.1128/spectrum.01102-22] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 07/19/2022] [Indexed: 12/24/2022] Open
Abstract
Wastewater-based epidemiology (WBE) has been widely used to track levels of SARS-CoV-2 infection in the community during the COVID-19 pandemic. Due to the rapid expansion of WBE, many methods have been used and developed for virus concentration and detection in wastewater. However, very little information is available on the relative performance of these approaches. In this study, we compared the performance of five commonly used wastewater concentration methods for the detection and quantification of pathogenic viruses (SARS-CoV-2, norovirus, rotavirus, influenza, and measles viruses), fecal indicator viruses (crAssphage, adenovirus, pepper mild mottle virus), and process control viruses (murine norovirus and bacteriophage Phi6) in laboratory spiking experiments. The methods evaluated included those based on either ultrafiltration (Amicon centrifugation units and InnovaPrep device) or precipitation (using polyethylene glycol [PEG], beef extract-enhanced PEG, and ammonium sulfate). The two best methods were further tested on 115 unspiked wastewater samples. We found that the volume and composition of the wastewater and the characteristics of the target viruses greatly affected virus recovery, regardless of the method used for concentration. All tested methods are suitable for routine virus concentration; however, the Amicon ultrafiltration method and the beef extract-enhanced PEG precipitation methods yielded the best recoveries. We recommend the use of ultrafiltration-based concentration for low sample volumes with high virus titers and ammonium levels and the use of precipitation-based concentration for rare pathogen detection in high-volume samples. IMPORTANCE As wastewater-based epidemiology is utilized for the surveillance of COVID-19 at the community level in many countries, it is crucial to develop and validate reliable methods for virus detection in sewage. The most important step in viral detection is the efficient concentration of the virus particles and/or their genome for subsequent analysis. In this study, we compared five different methods for the detection and quantification of different viruses in wastewater. We found that dead-end ultrafiltration and beef extract-enhanced polyethylene glycol precipitation were the most reliable approaches. We also discovered that sample volume and physico-chemical properties have a great effect on virus recovery. Hence, wastewater process methods and start volumes should be carefully selected in ongoing and future wastewater-based national surveillance programs for COVID-19 and beyond.
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Affiliation(s)
- Kata Farkas
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- School of Ocean Sciences, Bangor University, Anglesey, United Kingdom
| | - Cameron Pellett
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Natasha Alex-Sanders
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Matthew T. P. Bridgman
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Alexander Corbishley
- Royal (Dick) School of Veterinary Studies and The Roslin Institute, University of Edinburgh, Roslin, United Kingdom
| | - Jasmine M. S. Grimsley
- UK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom
| | | | - Jessica L. Kevill
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Igor Pântea
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - India S. Richardson-O’Neill
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Kathryn Lambert-Slosarska
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Nick Woodhall
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
| | - Davey L. Jones
- Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom
- Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
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32
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Fahrenfeld NL, Morales Medina WR, D'Elia S, Deshpande AS, Ehasz G. Year-long wastewater monitoring for SARS-CoV-2 signals in combined and separate sanitary sewers. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2022; 94:e10768. [PMID: 35918060 PMCID: PMC9350404 DOI: 10.1002/wer.10768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/07/2022] [Accepted: 07/01/2022] [Indexed: 05/14/2023]
Abstract
COVID-19 wastewater-based epidemiology has been performed in catchments of various sizes and sewer types with many short-term studies available and multi-seasonal studies emerging. The objective of this study was to compare weekly observations of SARS-CoV-2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS-CoV-2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non-sewer factors may be impacting the observations. In-system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow-normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. PRACTITIONER POINTS: SARS-CoV-2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level. Study performed when clinical testing was widespread during the year after the first COVID-19 wave in the region. Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater-based epidemiology results. Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.
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Affiliation(s)
- Nicole L. Fahrenfeld
- Department of Civil and Environmental EngineeringRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - William R. Morales Medina
- Department of Microbiology and Molecular GeneticsRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Present address:
American WaterDelranNew JerseyUSA
| | - Stephanie D'Elia
- Department of Biochemistry and MicrobiologyRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Aishwarya S. Deshpande
- Department of Biochemistry and MicrobiologyRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Genevieve Ehasz
- Department of Civil and Environmental EngineeringRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
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Fahrenfeld NL, Morales Medina WR, D'Elia S, Deshpande AS, Ehasz G. Year-long wastewater monitoring for SARS-CoV-2 signals in combined and separate sanitary sewers. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2022; 94:e10768. [PMID: 35918060 DOI: 10.1021/acsestwater.1c00345] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/07/2022] [Accepted: 07/01/2022] [Indexed: 05/27/2023]
Abstract
COVID-19 wastewater-based epidemiology has been performed in catchments of various sizes and sewer types with many short-term studies available and multi-seasonal studies emerging. The objective of this study was to compare weekly observations of SARS-CoV-2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS-CoV-2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non-sewer factors may be impacting the observations. In-system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow-normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. PRACTITIONER POINTS: SARS-CoV-2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level. Study performed when clinical testing was widespread during the year after the first COVID-19 wave in the region. Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater-based epidemiology results. Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.
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Affiliation(s)
- Nicole L Fahrenfeld
- Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - William R Morales Medina
- Department of Microbiology and Molecular Genetics, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Stephanie D'Elia
- Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Aishwarya S Deshpande
- Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Genevieve Ehasz
- Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
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