1
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Ram JL, Shuster W, Gable L, Turner CL, Hartrick J, Vasquez AA, West NW, Bahmani A, David RE. Wastewater Monitoring for Infectious Disease: Intentional Relationships between Academia, the Private Sector, and Local Health Departments for Public Health Preparedness. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6651. [PMID: 37681792 PMCID: PMC10487196 DOI: 10.3390/ijerph20176651] [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: 03/18/2023] [Revised: 06/29/2023] [Accepted: 07/20/2023] [Indexed: 09/09/2023]
Abstract
The public health emergency caused by the COVID-19 pandemic stimulated stakeholders from diverse disciplines and institutions to establish new collaborations to produce informed public health responses to the disease. Wastewater-based epidemiology for COVID-19 grew quickly during the pandemic and required the rapid implementation of such collaborations. The objective of this article is to describe the challenges and results of new relationships developed in Detroit, MI, USA among a medical school and an engineering college at an academic institution (Wayne State University), the local health department (Detroit Health Department), and an environmental services company (LimnoTech) to utilize markers of the COVID-19 virus, SARS-CoV-2, in wastewater for the goal of managing COVID-19 outbreaks. Our collaborative team resolved questions related to sewershed selection, communication of results, and public health responses and addressed technical challenges that included ground-truthing the sewer maps, overcoming supply chain issues, improving the speed and sensitivity of measurements, and training new personnel to deal with a new disease under pandemic conditions. Recognition of our complementary roles and clear communication among the partners enabled city-wide wastewater data to inform public health responses within a few months of the availability of funding in 2020, and to make improvements in sensitivity and understanding to be made as the pandemic progressed and evolved. As a result, the outbreaks of COVID-19 in Detroit in fall and winter 2021-2022 (corresponding to Delta and Omicron variant outbreaks) were tracked in 20 sewersheds. Data comparing community- and hospital-associated sewersheds indicate a one- to two-week advance warning in the community of subsequent peaks in viral markers in hospital sewersheds. The new institutional relationships impelled by the pandemic provide a good basis for continuing collaborations to utilize wastewater-based human and pathogen data for improving the public health in the future.
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Affiliation(s)
- Jeffrey L. Ram
- Department of Physiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA; (A.A.V.)
- Department of Biochemistry, Microbiology, and Immunology, Wayne State University, Detroit, MI 48201, USA
| | - William Shuster
- College of Engineering, Wayne State University, Detroit, MI 48202, USA;
| | - Lance Gable
- Law School, Wayne State University, Detroit, MI 48202, USA
| | | | | | - Adrian A. Vasquez
- Department of Physiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA; (A.A.V.)
| | - Nicholas W. West
- Department of Physiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA; (A.A.V.)
| | - Azadeh Bahmani
- Department of Physiology, School of Medicine, Wayne State University, Detroit, MI 48201, USA; (A.A.V.)
| | - Randy E. David
- Detroit Health Department, Detroit, MI 48201, USA
- Department of Family Medicine and Public Health Sciences, School of Medicine, Wayne State University, Detroit, MI 48201, USA
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2
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Kotay SM, Tanabe KO, Colosi LM, Poulter MD, Barry KE, Holstege CP, Mathers AJ, Porter MD. Building-Level Wastewater Surveillance for SARS-CoV-2 in Occupied University Dormitories as an Outbreak Forecasting Tool: One Year Case Study. ACS ES&T WATER 2022; 2:2094-2104. [PMID: 37552737 PMCID: PMC9212191 DOI: 10.1021/acsestwater.2c00057] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 06/03/2023]
Abstract
Congregate living poses one of the highest risk situations for the transmission of respiratory viruses including SARS-CoV-2. University dormitories exemplify such high-risk settings. We demonstrate the value of using building-level SARS-CoV-2 wastewater surveillance as an early warning system to inform when prevalence testing of all building occupants is warranted. Coordinated daily testing of composite wastewater samples and clinical testing in dormitories was used to prompt the screening of otherwise unrecognized infected occupants. We overlay the detection patterns in the context of regular scheduled occupant testing to validate a wastewater detection model. The trend of wastewater positivity largely aligned well with the clinical positivity and epidemiology of dormitory occupants. However, the predictive ability of wastewater-surveillance to detect new positive cases is hampered by convalescent shedding in recovered/noncontagious individuals as they return to the building. Building-level pooled wastewater-surveillance and forecasting is most productive for predicting new cases in low-prevalence instances at the community level. For higher-education facilities and other congregate living settings to remain in operation during a pandemic, a thorough surveillance-based decision-making system is vital. Building-level wastewater monitoring on a daily basis paired with regular testing of individual dormitory occupants is an effective and efficient approach for mitigating outbreaks on university campuses.
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Affiliation(s)
- Shireen M. Kotay
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Kawai O. Tanabe
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Lisa M. Colosi
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
| | - Melinda D. Poulter
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Katherine E. Barry
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
| | - Christopher P. Holstege
- Department of Student Health & Wellness, Division
of Student Affairs, University of Virginia, Charlottesville,
Virginia 22903, United States
- Departments of Emergency Medicine & Pediatrics,
School of Medicine, University of Virginia, Charlottesville,
Virginia 22903, United States
| | - Amy J. Mathers
- Division of Infectious Diseases, School of Medicine,
University of Virginia Health System, Charlottesville,
Virginia 22908, United States
- Clinical Microbiology Laboratory, Department of
Pathology, University of Virginia Health System,
Charlottesville, Virginia 22908, United States
| | - Michael D. Porter
- Department of Engineering Systems & Environment,
University of Virginia, Charlottesville, Virginia 22903,
United States
- School of Data Science, University of
Virginia, Charlottesville, Virginia 22903, United
States
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3
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Wartell BA, Proano C, Bakalian L, Kaya D, Croft K, McCreary M, Lichtenstein N, Miske V, Arcellana P, Boyer J, Benschoten IV, Anderson M, Crabb A, Gilson S, Gourley A, Wheeler T, Trest B, Bowman G, Kjellerup BV. Implementing wastewater surveillance for SARS-CoV-2 on a university campus: Lessons learned. WATER ENVIRONMENT RESEARCH : A RESEARCH PUBLICATION OF THE WATER ENVIRONMENT FEDERATION 2022; 94:e10807. [PMID: 36372781 PMCID: PMC9827968 DOI: 10.1002/wer.10807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/16/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
Wastewater surveillance, also known as wastewater-based epidemiology (WBE), has been successfully used to detect SARS-CoV-2 and other viruses in sewage in many locations in the United States and globally. This includes implementation of the surveillance on college and university campuses. A two-phase study was conducted during the 2020-2021 academic year to test the feasibility of a WBE system on campus and to supplement the clinical COVID-19 testing performed for the student, staff, and faculty body. The primary objective during the Fall 2020 semester was to monitor a large portion of the on-campus population and to obtain an understanding of the spreading of the SARS-CoV-2 virus. The Spring 2021 objective was focused on selected residence halls and groups of residents on campus, as this was more efficient and relevant for an effective follow-up response. Logistical problems and planning oversights initially occurred but were corrected with improved communication and experience. Many lessons were learned, including effective mapping, site planning, communication, personnel organization, and equipment management, and obtained along the way, thereby paving an opportune guide for future planning efforts. PRACTITIONER POINTS: WBE was successful in the detection of many SARS-CoV-2 variants incl. Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron. Careful planning and contingencies were essential for a successful implementation of a SARS-CoV-2 monitoring program. A surveillance program may be important for detection and monitoring of other public health relevant targets in wastewater incl. bacteria, viruses, fungi and viruses. Diverse lessons were learned incl. effective mapping, site planning, communication, personnel organization, and equipment management, thereby providing a guide for future planning efforts.
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Affiliation(s)
- Brian A. Wartell
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Camila Proano
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Lena Bakalian
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Devrim Kaya
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Kristen Croft
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Michael McCreary
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Naomi Lichtenstein
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Victoria Miske
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Patricia Arcellana
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Jessica Boyer
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Isabelle Van Benschoten
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Marya Anderson
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Andrea Crabb
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Susan Gilson
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Anthony Gourley
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Tim Wheeler
- Department of Residential FacilitiesUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Brian Trest
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Glynnis Bowman
- Facilities ManagementUniversity of Maryland College ParkCollege ParkMarylandUSA
| | - Birthe V. Kjellerup
- Department of Civil and Environmental EngineeringUniversity of Maryland College ParkCollege ParkMarylandUSA
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4
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Medina CY, Kadonsky KF, Roman FA, Tariqi AQ, Sinclair RG, D'Aoust PM, Delatolla R, Bischel HN, Naughton CC. The need of an environmental justice approach for wastewater based epidemiology for rural and disadvantaged communities: A review in California. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2022; 27:100348. [PMID: 35399703 PMCID: PMC8983025 DOI: 10.1016/j.coesh.2022.100348] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Amid the 2019 coronavirus disease pandemic (COVID-19), the scientific community has a responsibility to provide accessible public health resources within their communities. Wastewater based epidemiology (WBE) has been used to monitor community spread of the pandemic. The goal of this review was to evaluate the need for an environmental justice approach for COVID-19 WBE starting with the state of California in the United States. Methods included a review of the peer-reviewed literature, government-provided data, and news stories. As of June 2021, there were twelve universities, nine public dashboards, and 48 of 384 wastewater treatment plants monitoring wastewater for SARS-CoV-2 within California. The majority of wastewater monitoring in California has been conducted in the urban areas of Coastal and Southern California (34/48), with a lack of monitoring in more rural areas of Central (10/48) and Northern California (4/48). Similar to the access to COVID-19 clinical testing and vaccinations, there is a disparity in access to wastewater testing which can often provide an early warning system to outbreaks. This research demonstrates the need for an environmental justice approach and equity considerations when determining locations for environmental monitoring.
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Affiliation(s)
- Clara Y Medina
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA
| | - Krystin F Kadonsky
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA
| | - Fernando A Roman
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA
| | - Arianna Q Tariqi
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA
| | - Ryan G Sinclair
- School of Public Health, Loma Linda University, Linda, California, USA
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, CA, USA
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, Ontario, CA, USA
| | - Heather N Bischel
- Department of Civil and Environmental Engineering, University of California Davis, Davis, CA, USA
| | - Colleen C Naughton
- Department of Civil and Environmental Engineering, University of California Merced, Merced, CA, USA
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5
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Xiao A, Wu F, Bushman M, Zhang J, Imakaev M, Chai PR, Duvallet C, Endo N, Erickson TB, Armas F, Arnold B, Chen H, Chandra F, Ghaeli N, Gu X, Hanage WP, Lee WL, Matus M, McElroy KA, Moniz K, Rhode SF, Thompson J, Alm EJ. Metrics to relate COVID-19 wastewater data to clinical testing dynamics. WATER RESEARCH 2022; 212:118070. [PMID: 35101695 PMCID: PMC8758950 DOI: 10.1016/j.watres.2022.118070] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 11/29/2021] [Accepted: 01/11/2022] [Indexed: 05/02/2023]
Abstract
Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.
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Affiliation(s)
- Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology USA
| | - Fuqing Wu
- Department of Biological Engineering, Massachusetts Institute of Technology USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology USA
| | - Mary Bushman
- Harvard T.H. Chan School of Public Health, Harvard University USA
| | - Jianbo Zhang
- Department of Biological Engineering, Massachusetts Institute of Technology USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology USA
| | | | - Peter R Chai
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School USA; The Fenway Institute, Fenway Health, Boston, MA USA; The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology USA; Department of Psychosocial Oncology and Palliative Care, Dana Farber Cancer Institute USA
| | | | | | - Timothy B Erickson
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School USA; Harvard Humanitarian Initiative, Harvard University USA
| | - Federica Armas
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Brian Arnold
- Department of Computer Science, Princeton University USA; Center for Statistics and Machine Learning, Princeton University USA
| | - Hongjie Chen
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Franciscus Chandra
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | | | - Xiaoqiong Gu
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - William P Hanage
- Harvard T.H. Chan School of Public Health, Harvard University USA
| | - Wei Lin Lee
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | | | | | - Katya Moniz
- Department of Biological Engineering, Massachusetts Institute of Technology USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology USA
| | | | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology USA; Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Broad Institute of MIT and Harvard, Cambridge, MA USA.
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6
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Olesen SW, Imakaev M, Duvallet C. Making waves: Defining the lead time of wastewater-based epidemiology for COVID-19. WATER RESEARCH 2021; 202:117433. [PMID: 34304074 PMCID: PMC8282235 DOI: 10.1016/j.watres.2021.117433] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/24/2021] [Accepted: 07/09/2021] [Indexed: 05/19/2023]
Abstract
Individuals infected with SARS-CoV-2, the virus that causes COVID-19, may shed the virus in stool before developing symptoms, suggesting that measurements of SARS-CoV-2 concentrations in wastewater could be a "leading indicator" of COVID-19 prevalence. Multiple studies have corroborated the leading indicator concept by showing that the correlation between wastewater measurements and COVID-19 case counts is maximized when case counts are lagged. However, the meaning of "leading indicator" will depend on the specific application of wastewater-based epidemiology, and the correlation analysis is not relevant for all applications. In fact, the quantification of a leading indicator will depend on epidemiological, biological, and health systems factors. Thus, there is no single "lead time" for wastewater-based COVID-19 monitoring. To illustrate this complexity, we enumerate three different applications of wastewater-based epidemiology for COVID-19: a qualitative "early warning" system; an independent, quantitative estimate of disease prevalence; and a quantitative alert of bursts of disease incidence. The leading indicator concept has different definitions and utility in each application.
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7
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Gibas C, Lambirth K, Mittal N, Juel MAI, Barua VB, Roppolo Brazell L, Hinton K, Lontai J, Stark N, Young I, Quach C, Russ M, Kauer J, Nicolosi B, Chen D, Akella S, Tang W, Schlueter J, Munir M. Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 782:146749. [PMID: 33838367 PMCID: PMC8007530 DOI: 10.1016/j.scitotenv.2021.146749] [Citation(s) in RCA: 166] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 03/20/2021] [Accepted: 03/21/2021] [Indexed: 05/17/2023]
Abstract
The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.
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Affiliation(s)
- Cynthia Gibas
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Bioinformatics Research Center, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America.
| | - Kevin Lambirth
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America.
| | - Neha Mittal
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Md Ariful Islam Juel
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Visva Bharati Barua
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Lauren Roppolo Brazell
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Keshawn Hinton
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jordan Lontai
- Department of Geography and Earth Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Nicholas Stark
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Isaiah Young
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Cristine Quach
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Morgan Russ
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jacob Kauer
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Bridgette Nicolosi
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Don Chen
- Department of Engineering Technology and Construction Management, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Srinivas Akella
- Department of Computer Science, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Wenwu Tang
- Department of Geography and Earth Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Center for Applied Geographic Information Systems, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jessica Schlueter
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Bioinformatics Research Center, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Mariya Munir
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
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8
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Gibas C, Lambirth K, Mittal N, Juel MAI, Barua VB, Roppolo Brazell L, Hinton K, Lontai J, Stark N, Young I, Quach C, Russ M, Kauer J, Nicolosi B, Chen D, Akella S, Tang W, Schlueter J, Munir M. Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 782:146749. [PMID: 33838367 DOI: 10.1101/2020.12.31.20248843] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 03/20/2021] [Accepted: 03/21/2021] [Indexed: 05/18/2023]
Abstract
The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.
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Affiliation(s)
- Cynthia Gibas
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Bioinformatics Research Center, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America.
| | - Kevin Lambirth
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America.
| | - Neha Mittal
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Md Ariful Islam Juel
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Visva Bharati Barua
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Lauren Roppolo Brazell
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Keshawn Hinton
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jordan Lontai
- Department of Geography and Earth Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Nicholas Stark
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Isaiah Young
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Cristine Quach
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Morgan Russ
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jacob Kauer
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Bridgette Nicolosi
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Don Chen
- Department of Engineering Technology and Construction Management, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Srinivas Akella
- Department of Computer Science, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Wenwu Tang
- Department of Geography and Earth Sciences, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Center for Applied Geographic Information Systems, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Jessica Schlueter
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America; Bioinformatics Research Center, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
| | - Mariya Munir
- Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, United States of America
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9
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Xiao A, Wu F, Bushman M, Zhang J, Imakaev M, Chai PR, Duvallet C, Endo N, Erickson TB, Armas F, Arnold B, Chen H, Chandra F, Ghaeli N, Gu X, Hanage WP, Lee WL, Matus M, McElroy KA, Moniz K, Rhode SF, Thompson J, Alm EJ. Metrics to relate COVID-19 wastewater data to clinical testing dynamics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.06.10.21258580. [PMID: 34159339 PMCID: PMC8219106 DOI: 10.1101/2021.06.10.21258580] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.
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Affiliation(s)
- Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | - Fuqing Wu
- Department of Biological Engineering, Massachusetts Institute of Technology
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | - Mary Bushman
- Harvard T.H. Chan School of Public Health, Harvard University
| | - Jianbo Zhang
- Department of Biological Engineering, Massachusetts Institute of Technology
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | | | - Peter R Chai
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School
- The Fenway Institute, Fenway Health, Boston, MA
- The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology
- Department of Psychosocial Oncology and Palliative Care, Dana Farber Cancer Institute
| | | | | | - Timothy B Erickson
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women’s Hospital, Harvard Medical School
- Harvard Humanitarian Initiative, Harvard University
| | - Federica Armas
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Brian Arnold
- Department of Computer Science, Princeton University
- Center for Statistics and Machine Learning, Princeton University
| | - Hongjie Chen
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | - Franciscus Chandra
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | | | - Xiaoqiong Gu
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | | | - Wei Lin Lee
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
| | | | | | - Katya Moniz
- Department of Biological Engineering, Massachusetts Institute of Technology
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
| | | | - Janelle Thompson
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
- Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
- Broad Institute of MIT and Harvard, Cambridge, MA
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