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Combe M, Cherif E, Deremarque T, Rivera-Ingraham G, Seck-Thiam F, Justy F, Doudou JC, Carod JF, Carage T, Procureur A, Gozlan RE. Wastewater sequencing as a powerful tool to reveal SARS-CoV-2 variant introduction and spread in French Guiana, South America. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171645. [PMID: 38479523 DOI: 10.1016/j.scitotenv.2024.171645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/19/2024] [Accepted: 03/09/2024] [Indexed: 03/17/2024]
Abstract
The origin of introduction of a new pathogen in a country, the evolutionary dynamics of an epidemic within a country, and the role of cross-border areas on pathogen dynamics remain complex to disentangle and are often poorly understood. For instance, cross-border areas represent the ideal location for the sharing of viral variants between countries, with international air travel, land travel and waterways playing an important role in the cross-border spread of infectious diseases. Unfortunately, monitoring the point of entry and the evolutionary dynamics of viruses in space and time within local populations remain challenging. Here we tested the efficiency of wastewater-based epidemiology and genotyping in monitoring Covid-19 epidemiology and SARS-CoV-2 variant dynamics in French Guiana, a tropical country located in South America. Our results suggest that wastewater-based epidemiology and genotyping are powerful tools to monitor variant introduction and disease evolution within a tropical country but the inclusion of both clinical and wastewater samples could still improve our understanding of genetic diversity co-circulating. Wastewater sequencing also revealed the cryptic transmission of SARS-CoV-2 variants within the country. Interestingly, we found some amino acid changes specific to the variants co-circulating in French Guiana, suggesting a local evolution of the SARS-CoV-2 variants after their introduction. More importantly, our results showed that the proximity to bordering countries was not the origin of the emergence of the French Guianese B.1.160.25 variant, but rather that this variant emerged from an ancestor B.1.160 variant introduced by European air plane travelers, suggesting thus that air travel remains a significant risk for cross-border spread of infectious diseases. Overall, we suggest that wastewater-based epidemiology and genotyping provides a cost effective and non-invasive approach for pathogen monitoring and an early-warning tool for disease emergence and spread within a tropical country.
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Affiliation(s)
- Marine Combe
- ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France.
| | - Emira Cherif
- ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France
| | | | - Georgina Rivera-Ingraham
- ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France; Centre IRD de Cayenne, Guyane Française, France
| | | | | | | | - Jean-François Carod
- Laboratoire et Pôle Appui aux Fonctions Cliniques, Centre Hospitalier de l'Ouest Guyanais (CHOG), 97320 Saint-Laurent du Maroni, Guyane Française, France
| | - Thierry Carage
- Laboratoire de Biologie Médicale Carage de Kourou, 6 avenue Leopold Heder, 97310 Kourou, Guyane Française, France
| | - Angélique Procureur
- Laboratoire de Biologie Médicale Carage de Kourou, 6 avenue Leopold Heder, 97310 Kourou, Guyane Française, France
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2
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Zammit I, Badia S, Mejías-Molina C, Rusiñol M, Bofill-Mas S, Borrego CM, Corominas L. Zooming in to the neighborhood level: A year-long wastewater-based epidemiology monitoring campaign for COVID-19 in small intraurban catchments. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167811. [PMID: 37852481 DOI: 10.1016/j.scitotenv.2023.167811] [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: 06/08/2023] [Revised: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 10/20/2023]
Abstract
In recent years, wastewater-based epidemiology (WBE) has emerged as a valuable and cost-effective tool for monitoring the prevalence of COVID-19. Large-scale monitoring efforts have been implemented in numerous countries, primarily focusing on sampling at the entrance of wastewater treatment plants (WWTPs) to cover a large population. However, sampling at a finer spatial scale, such as at the neighborhood level (NGBs), pose new challenges, including the absence of composite sampling infrastructure and increased uncertainty due to the dynamics of small catchments. This study aims to investigate the feasibility and accuracy of WBE when deployed at the neighborhood level (sampling in sewers) compared to the city level (sampling at the entrance of a WWTP). To achieve this, we deployed specific WBE sampling stations at the intraurban scale within three NGBs in Barcelona, Spain. The study period covers the 5th and the 6th waves of COVID-19 in Spain, spanning from March 2021 to March 2022, along with the WWTP downstream from the NGBs. The results showed a strong correlation between the dynamics of COVID-19 clinical cases and wastewater SARS-CoV-2 loads at both the NGB and city levels. Notably, during the 5th wave, which was dominated by the Delta SARS-CoV-2 variant, wastewater loads were higher than during the 6th wave (Omicron variant), despite a lower number of clinical cases recorded during the 5th wave. The correlations between wastewater loads and clinical cases at the NGB level were stronger than at the WWTP level. However, the early warning potential varied across neighborhoods and waves, with some cases showing a one-week early warning and others lacking any significant early warning signal. Interestingly, the prevalence of COVID-19 did not exhibit major differences among NGBs with different socioeconomic statuses.
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Affiliation(s)
- Ian Zammit
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain
| | - Sergi Badia
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain
| | - Cristina Mejías-Molina
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Marta Rusiñol
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Sílvia Bofill-Mas
- Laboratory of Viruses Contaminants of Water and Food, Genetics, Microbiology & Statistics Dept., Universitat de Barcelona, Barcelona, Catalonia, Spain; The Water Research Institute (IdRA), Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Carles M Borrego
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; Group of Molecular Microbial Ecology, Institute of Aquatic Ecology, University of Girona, Girona, Catalonia, Spain
| | - Lluís Corominas
- Catalan Institute for Water Research (ICRA-CERCA), Emili Grahit 101, 17003 Girona, Spain; University of Girona, Plaça de Sant Domènec 3, 17004 Girona, Spain.
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3
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König AW, Ariano SS, Joksimovic D. Analysis of sampling strategies for pulse loads of SARS-CoV-2: implications for wastewater-based epidemiology. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2023; 88:1039-1057. [PMID: 37651336 PMCID: wst_2023_233 DOI: 10.2166/wst.2023.233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
A faecal transport model was applied to a 11.3 km2 wastewater servicing area in Toronto, Ontario, Canada to explore the role that different wastewater sampling campaigns have on estimating the prevalence of SARS-CoV-2 in a population of 60,000. A stochastic wastewater and water quality model was used to evaluate the effectiveness of 11 sampling campaigns during periods of high and low COVID-19 infection among the population, tested using virtual sampling during dry-weather flow. The virtual sampling campaigns were based on the most common automatic sampler programming capabilities and widely used wastewater-based epidemiology (WBE) sampling campaigns reported in the literature. Sampling campaigns differ in weighting method (time, volume, or flow-weighted sampling), sample count, collection period, or sample time. Results suggest that grab samples should be avoided and/or that sampling campaigns with the greatest sample counts and durations are the most robust at capturing COVID-19 infection among the population. Most surprisingly, changes to the weighting method were negligible indicating that a greater number of samples, and larger sample volumes are preferred. This work suggests that investment in flow monitoring equipment for flow- or volume-weighted sampling will not improve WBE results, and that standard time based sampling is sufficient.
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Affiliation(s)
- Albert Wilhelm König
- Institute of Urban Water Management and Landscape Water Engineering, Graz University of Technolog, Stremayrgasse 10/1, Graz 8010, Austria E-mail:
| | - Sarah Sydney Ariano
- Department of Earth and Planetary Sciences, McGill University, 3450 University Street, Montreal, QC, H3A 0E8, Canada
| | - Darko Joksimovic
- Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
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4
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Jiang G, Liu Y, Tang S, Kitajima M, Haramoto E, Arora S, Choi PM, Jackson G, D'Aoust PM, Delatolla R, Zhang S, Guo Y, Wu J, Chen Y, Sharma E, Prosun TA, Zhao J, Kumar M, Honda R, Ahmed W, Meiman J. Moving forward with COVID-19: Future research prospects of wastewater-based epidemiology methodologies and applications. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2023; 33:100458. [PMID: 37034453 PMCID: PMC10065412 DOI: 10.1016/j.coesh.2023.100458] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Wastewater-based epidemiology (WBE) has been demonstrated for its great potential in tracking of coronavirus disease 2019 (COVID-19) transmission among populations despite some inherent methodological limitations. These include non-optimized sampling approaches and analytical methods; stability of viruses in sewer systems; partitioning/retention in biofilms; and the singular and inaccurate back-calculation step to predict the number of infected individuals in the community. Future research is expected to (1) standardize best practices in wastewater sampling, analysis and data reporting protocols for the sensitive and reproducible detection of viruses in wastewater; (2) understand the in-sewer viral stability and partitioning under the impacts of dynamic wastewater flow, properties, chemicals, biofilms and sediments; and (3) achieve smart wastewater surveillance with artificial intelligence and big data models. Further specific research is essential in the monitoring of other viral pathogens with pandemic potential and subcatchment applications to maximize the benefits of WBE beyond COVID-19.
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Affiliation(s)
- Guangming Jiang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Yanchen Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health (NIEH), Chinese Center for Disease Control and Prevention (China CDC), Chaoyang District, Beijing 100021, China
| | - Masaaki Kitajima
- Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, North 13 West 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan
| | - Eiji Haramoto
- Interdisciplinary Center for River Basin Environment, University of Yamanashi, 4-3-11 Takeda, Kofu, Yamanashi 400-8511, Japan
| | - Sudipti Arora
- Dr. B. Lal Institute of Biotechnology, 6-E, Malviya Industrial Area, Malviya Nagar, Jaipur, 302017, India
| | - Phil M Choi
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Australia
| | - Greg Jackson
- Water Unit, Health Protection Branch, Queensland Public Health and Scientific Services, Queensland Health, Australia
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, Canada
| | - Shuxin Zhang
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Ying Guo
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Jiangping Wu
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Yan Chen
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Elipsha Sharma
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Tanjila Alam Prosun
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Jiawei Zhao
- School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Manish Kumar
- Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Campus Monterey, Monterrey, 64849, Nuevo Leon, Mexico
| | - Ryo Honda
- Faculty of Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan
| | - Warish Ahmed
- CSIRO Environment, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia
| | - Jon Meiman
- Wisconsin Department of Health Services, Madison, WI 53701, USA
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5
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Kotlarz N, Holcomb DA, Tanvir Pasha ABM, Reckling S, Kays J, Lai YC, Daly S, Palani S, Bailey E, Guidry VT, Christensen A, Berkowitz S, Hoppin JA, Mitasova H, Engel LS, Reyes FLDL, Harris A. Timing and Trends for Municipal Wastewater, Lab-Confirmed Case, and Syndromic Case Surveillance of COVID-19 in Raleigh, North Carolina. Am J Public Health 2023; 113:79-88. [PMID: 36356280 PMCID: PMC9755929 DOI: 10.2105/ajph.2022.307108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/26/2022] [Indexed: 11/12/2022]
Abstract
Objectives. To compare 4 COVID-19 surveillance metrics in a major metropolitan area. Methods. We analyzed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater influent and primary solids in Raleigh, North Carolina, from April 10 through December 13, 2020. We compared wastewater results with lab-confirmed COVID-19 cases and syndromic COVID-like illness (CLI) cases to answer 3 questions: (1) Did they correlate? (2) What was the temporal alignment of the different surveillance systems? (3) Did periods of significant change (i.e., trends) align? Results. In the Raleigh sewershed, wastewater influent, wastewater primary solids, lab-confirmed cases, and CLI were strongly or moderately correlated. Trends in lab-confirmed cases and wastewater influent were observed earlier, followed by CLI and, lastly, wastewater primary solids. All 4 metrics showed sustained increases in COVID-19 in June, July, and November 2020 and sustained decreases in August and September 2020. Conclusions. In a major metropolitan area in 2020, the timing of and trends in municipal wastewater, lab-confirmed case, and syndromic case surveillance of COVID-19 were in general agreement. Public Health Implications. Our results provide evidence for investment in SARS-CoV-2 wastewater and CLI surveillance to complement information provided through lab-confirmed cases. (Am J Public Health. 2023;113(1):79-88. https://doi.org/10.2105/AJPH.2022.307108).
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Affiliation(s)
- Nadine Kotlarz
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - David A Holcomb
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - A B M Tanvir Pasha
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Stacie Reckling
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Judith Kays
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Yi-Chun Lai
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Sean Daly
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Sivaranjani Palani
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Erika Bailey
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Virginia T Guidry
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Ariel Christensen
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Steven Berkowitz
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Jane A Hoppin
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Helena Mitasova
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Lawrence S Engel
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Francis L de Los Reyes
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
| | - Angela Harris
- Nadine Kotlarz and Jane A. Hoppin are with the Department of Biological Sciences, North Carolina State University, Raleigh. David A. Holcomb and Lawrence S. Engel are with the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. A. B. M. Tanvir Pasha, Judith Kays, Yi-Chun Lai, Sean Daly, Francis L. de los Reyes III, and Angela Harris are with the Department of Civil, Construction, and Environmental Engineering, North Carolina State University. Stacie Reckling and Helena Mitasova are with the Center for Geospatial Analytics, North Carolina State University. Sivaranjani Palani is with the Department of Plant and Microbial Biology, North Carolina State University. Erika Bailey is with Raleigh Water, Raleigh, NC. Virginia T. Guidry, Ariel Christensen, and Steven Berkowitz are with the Division of Public Health, North Carolina Department of Health and Human Services, Raleigh
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6
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Hoar C, McClary-Gutierrez J, Wolfe MK, Bivins A, Bibby K, Silverman AI, McLellan SL. Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:125002. [PMID: 36580023 PMCID: PMC9799055 DOI: 10.1289/ehp11519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. OBJECTIVES We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system. DISCUSSION Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.
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Affiliation(s)
- Catherine Hoar
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Jill McClary-Gutierrez
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
| | - Marlene K. Wolfe
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Aaron Bivins
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Kyle Bibby
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Indiana, USA
| | - Andrea I. Silverman
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, New York, USA
| | - Sandra L. McLellan
- School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
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7
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Kotay SM, Tanabe KO, Colosi LM, Poulter MD, Barry KE, Holstege CP, Mathers AJ, Porter MD. Building-Level Wastewater Surveillance for SARS-CoV-2 in Occupied University Dormitories as an Outbreak Forecasting Tool: One Year Case Study. ACS ES&T WATER 2022; 2:2094-2104. [PMID: 37552737 PMCID: PMC9212191 DOI: 10.1021/acsestwater.2c00057] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 06/03/2023]
Abstract
Congregate living poses one of the highest risk situations for the transmission of respiratory viruses including SARS-CoV-2. University dormitories exemplify such high-risk settings. We demonstrate the value of using building-level SARS-CoV-2 wastewater surveillance as an early warning system to inform when prevalence testing of all building occupants is warranted. Coordinated daily testing of composite wastewater samples and clinical testing in dormitories was used to prompt the screening of otherwise unrecognized infected occupants. We overlay the detection patterns in the context of regular scheduled occupant testing to validate a wastewater detection model. The trend of wastewater positivity largely aligned well with the clinical positivity and epidemiology of dormitory occupants. However, the predictive ability of wastewater-surveillance to detect new positive cases is hampered by convalescent shedding in recovered/noncontagious individuals as they return to the building. Building-level pooled wastewater-surveillance and forecasting is most productive for predicting new cases in low-prevalence instances at the community level. For higher-education facilities and other congregate living settings to remain in operation during a pandemic, a thorough surveillance-based decision-making system is vital. Building-level wastewater monitoring on a daily basis paired with regular testing of individual dormitory occupants is an effective and efficient approach for mitigating outbreaks on university campuses.
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Affiliation(s)
- Shireen M. Kotay
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Kawai O. Tanabe
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Lisa M. Colosi
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
| | - Melinda D. Poulter
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Katherine E. Barry
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Christopher P. Holstege
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
- Departments of Emergency Medicine & Pediatrics,
School of Medicine, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Amy J. Mathers
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Michael D. Porter
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
- School of Data Science, University of
Virginia, Charlottesville, Virginia 22903, United
States
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8
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Acer PT, Kelly LM, Lover AA, Butler CS. Quantifying the Relationship between SARS-CoV-2 Wastewater Concentrations and Building-Level COVID-19 Prevalence at an Isolation Residence: A Passive Sampling Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11245. [PMID: 36141515 PMCID: PMC9517461 DOI: 10.3390/ijerph191811245] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/23/2022] [Accepted: 08/26/2022] [Indexed: 05/26/2023]
Abstract
SARS-CoV-2 RNA loads can be detected in the excreta of individuals with COVID-19 and have demonstrated positive correlations with clinical infection trends. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor community-level prevalence of infections. The majority of wastewater specimens are gathered as either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and can be challenging to maintain in cold weather, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Passive sampling can provide an affordable, practical, and scalable sampling system while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from 1 February 2021-21 May 2021. Samples (n = 64) were collected 3-5 times weekly and remained within the sewer for a median duration of 24 h. SARS-CoV-2 RNA was quantified using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) targeting the N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform building-level public health responses.
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Affiliation(s)
- Patrick T. Acer
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst, MA 01003, USA
| | - Lauren M. Kelly
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst, MA 01003, USA
| | - Andrew A. Lover
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst, MA 01003, USA
| | - Caitlyn S. Butler
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst, MA 01003, USA
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9
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Dai X, Champredon D, Fazil A, Mangat CS, Peterson SW, Mejia EM, Lu X, Chekouo T. Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater. Sci Rep 2022; 12:13490. [PMID: 35931713 PMCID: PMC9355971 DOI: 10.1038/s41598-022-17543-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/27/2022] [Indexed: 11/23/2022] Open
Abstract
The ribonucleic acid (RNA) of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is detectable in municipal wastewater as infected individuals can shed the virus in their feces. Viral concentration in wastewater can inform the severity of the COVID-19 pandemic but observations can be noisy and sparse and hence hamper the epidemiological interpretation. Motivated by a Canadian nationwide wastewater surveillance data set, unlike previous studies, we propose a novel Bayesian statistical framework based on the theories of functional data analysis to tackle the challenges embedded in the longitudinal wastewater monitoring data. By employing this framework to analyze the large-scale data set from the nationwide wastewater surveillance program covering 15 sampling sites across Canada, we successfully detect the true trends of viral concentration out of noisy and sparsely observed viral concentrations, and accurately forecast the future trajectory of viral concentrations in wastewater. Along with the excellent performance assessment using simulated data, this study shows that the proposed novel framework is a useful statistical tool and has a significant potential in supporting the epidemiological interpretation of noisy viral concentration measurements from wastewater samples in a real-life setting.
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Affiliation(s)
- Xiaotian Dai
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
| | - David Champredon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Chand S Mangat
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Shelley W Peterson
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Edgard M Mejia
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Xuewen Lu
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
| | - Thierry Chekouo
- Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada.
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10
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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: 0.3] [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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11
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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: 13] [Impact Index Per Article: 4.3] [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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12
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Acer PT, Kelly LM, Lover AA, Butler CS. Quantifying the relationship between SARS-CoV-2 wastewater concentrations and building-level COVID-19 prevalence at an isolation residence using a passive sampling approach. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.04.07.22273534. [PMID: 35441165 PMCID: PMC9016645 DOI: 10.1101/2022.04.07.22273534] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
SARS-CoV-2 RNA can be detected in the excreta of individuals with COVID-19 and has demonstrated a positive correlation with various clinical parameters. Consequently, wastewater-based epidemiology (WBE) approaches have been implemented globally as a public health surveillance tool to monitor the community-level prevalence of infections. Over 270 higher education campuses monitor wastewater for SARS-CoV-2, with most gathering either composite samples via automatic samplers (autosamplers) or grab samples. However, autosamplers are expensive and challenging to manage with seasonal variability, while grab samples are particularly susceptible to temporal variation when sampling sewage directly from complex matrices outside residential buildings. Prior studies have demonstrated encouraging results utilizing passive sampling swabs. Such methods can offer affordable, practical, and scalable alternatives to traditional methods while maintaining a reproducible SARS-CoV-2 signal. In this regard, we deployed tampons as passive samplers outside of a COVID-19 isolation unit (a segregated residence hall) at a university campus from February 1, 2021 â€" May 21, 2021. Samples were collected several times weekly and remained within the sewer for a minimum of 24 hours (n = 64). SARS-CoV-2 RNA was quantified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) targeting the viral N1 and N2 gene fragments. We quantified the mean viral load captured per individual and the association between the daily viral load and total persons, adjusting for covariates using multivariable models to provide a baseline estimate of viral shedding. Samples were processed through two distinct laboratory pipelines on campus, yielding highly correlated N2 concentrations. Data obtained here highlight the success of passive sampling utilizing tampons to capture SARS-CoV-2 in wastewater coming from a COVID-19 isolation residence, indicating that this method can help inform public health responses in a range of settings. Highlights Daily SARS-CoV-2 RNA loads in building-level wastewater were positively associated with the total number of COVID-19 positive individuals in the residenceThe variation in individual fecal shedding rates of SARS-CoV-2 extended four orders of magnitudeWastewater sample replicates were highly correlated using distinct processing pipelines in two independent laboratoriesWhile the isolation residence was occupied, SARS-CoV-2 RNA was detected in all passive samples.
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Affiliation(s)
- Patrick T Acer
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst MA 01003, U.S
| | - Lauren M Kelly
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst MA 01003, U.S
| | - Andrew A Lover
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Arnold House, 715 North Pleasant Street, Amherst MA 01003, U.S
| | - Caitlyn S Butler
- Department of Environmental and Water Resources Engineering, University of Massachusetts Amherst, Engineering Lab II, 101 N Service Rd, Amherst MA 01003, U.S
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13
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Fahrenfeld NL, Morales Medina WR, D'Elia S, Modica M, Ruiz A, McLane M. Comparison of residential dormitory COVID-19 monitoring via weekly saliva testing and sewage monitoring. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 814:151947. [PMID: 34838560 PMCID: PMC8611854 DOI: 10.1016/j.scitotenv.2021.151947] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/05/2021] [Accepted: 11/20/2021] [Indexed: 05/09/2023]
Abstract
Wastewater surveillance has been used as a tool for COVID-19 outbreak detection particularly where there was not capability in place for routine and robust individual testing. Given clinical reports that earlier detection is possible following infection from throat/nasal samples compared to fecal samples for COVID-19 patients, the utility of wastewater testing where robust individual testing is possible is less clear. The objective of this study was to compare the results of weekly required COVID-19 saliva tests to weekly wastewater monitoring for residential buildings (i.e., dormitories) located across three college campuses capturing wastewater from 80 to 441 occupants per sampling location. Sampling occurred during the spring semester of the 2021 academic year which captured the third wave of SARS-CoV-2 cases in the study region. Comparison of the saliva and wastewater testing results indicated that the wastewater SARS-CoV-2 concentrations had a strong linear correlation with the previous week's percentage of positive saliva test results and a weak linear correlation with the saliva testing results surrounding the wastewater sampling (four days before and 3 days after). Given that no correlation was observed between the wastewater and the saliva testing from the following week, the weekly saliva testing captured spikes in COVID-19 cases earlier than the weekly wastewater sampling. Interestingly, the N1 gene was observed in buildings on all campuses, but N2 was observed in wastewater on only one of the campuses. N1 and N2 were also observed in sewer biofilm. The campus-specific challenges associated with implementation of wastewater surveillance are discussed. Overall, these results can help inform design of surveillance for early detection of SARS-CoV-2 in residential settings thereby informing mitigation strategies to slow or prevent the spread of the virus among residents in congregate living.
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Affiliation(s)
- N L Fahrenfeld
- Civil & Environmental Engineering, Rutgers, The State University of New Jersey, 500 Bartholomew Dr, Piscataway, NJ 08854, USA.
| | | | - Stephanie D'Elia
- Biochemistry and Microbiology, Rutgers, The State University of New Jersey, USA
| | - Maureen Modica
- Environmental Health and Safety, Rutgers, The State University of New Jersey, USA
| | - Alejandro Ruiz
- Environmental Health and Safety, Rutgers, The State University of New Jersey, USA
| | - Mark McLane
- Environmental Health and Safety, Rutgers, The State University of New Jersey, USA
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