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Baldwin WM, Dayton RD, Bivins AW, Scott RS, Yurochko AD, Vanchiere JA, Davis T, Arnold CL, Asuncion JET, Bhuiyan MAN, Snead B, Daniel W, Smith DG, Goeders NE, Kevil CG, Carroll J, Murnane KS. Highly socially vulnerable communities exhibit disproportionately increased viral loads as measured in community wastewater. ENVIRONMENTAL RESEARCH 2023; 222:115351. [PMID: 36709030 PMCID: PMC9877155 DOI: 10.1016/j.envres.2023.115351] [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: 07/15/2022] [Revised: 01/12/2023] [Accepted: 01/22/2023] [Indexed: 06/18/2023]
Abstract
Wastewater surveillance has proven to be a useful tool for evidence-based epidemiology in the fight against the SARS-CoV-2 virus. It is particularly useful at the population level where acquisition of individual test samples may be time or cost-prohibitive. Wastewater surveillance for SARS-CoV-2 has typically been performed at wastewater treatment plants; however, this study was designed to sample on a local level to monitor the spread of the virus among three communities with distinct social vulnerability indices in Shreveport, Louisiana, located in a socially vulnerable region of the United States. Twice-monthly grab samples were collected from September 30, 2020, to March 23, 2021, during the Beta wave of the pandemic. The goals of the study were to examine whether: 1) concentrations of SARS-CoV-2 RNA in wastewater varied with social vulnerability indices and, 2) the time lag of spikes differed during wastewater monitoring in the distinct communities. The size of the population contributing to each sample was assessed via the quantification of the pepper mild mottle virus (PMMoV), which was significantly higher in the less socially vulnerable community. We found that the communities with higher social vulnerability exhibited greater viral loads as assessed by wastewater when normalized with PMMoV (Kruskal-Wallis, p < 0.05). The timing of the spread of the virus through the three communities appeared to be similar. These results suggest that interconnected communities within a municipality experienced the spread of the SARS-CoV-2 virus at similar times, but areas of high social vulnerability experienced more intense wastewater viral loads.
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Affiliation(s)
- William M Baldwin
- Department of Pharmacology, Toxicology & Neuroscience, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Robert D Dayton
- Department of Pharmacology, Toxicology & Neuroscience, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Aaron W Bivins
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Rona S Scott
- Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Microbiology and Immunology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Andrew D Yurochko
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Division of Health Disparities, Department of Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - John A Vanchiere
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Division of Infectious Diseases, Department of Pediatrics, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Terry Davis
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Division of Health Disparities, Department of Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Connie L Arnold
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Division of Health Disparities, Department of Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Jose E T Asuncion
- Department of Public Health, School of Allied Health Professions, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Mohammad A N Bhuiyan
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Division of Clinical Informatics, Department of Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Brandon Snead
- Department of Water and Sewage, City of Shreveport, Shreveport, Louisiana, USA
| | - William Daniel
- Department of Water and Sewage, City of Shreveport, Shreveport, Louisiana, USA
| | - Deborah G Smith
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Public Health, School of Allied Health Professions, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Nicholas E Goeders
- Department of Pharmacology, Toxicology & Neuroscience, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Psychiatry & Behavioral Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Christopher G Kevil
- Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Pathology, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Molecular and Cellular Physiology, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Cell Biology and Anatomy, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Jennifer Carroll
- Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA
| | - Kevin S Murnane
- Department of Pharmacology, Toxicology & Neuroscience, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Louisiana Addiction Research Center, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Center of Excellence for Emerging Viral Threats, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Psychiatry & Behavioral Medicine, School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA; Department of Cell Biology and Anatomy, School of Graduate Studies, Louisiana State University Health Sciences Center at Shreveport, Shreveport, Louisiana, USA.
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2
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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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3
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Castro-Gutierrez V, Hassard F, Vu M, Leitao R, Burczynska B, Wildeboer D, Stanton I, Rahimzadeh S, Baio G, Garelick H, Hofman J, Kasprzyk-Hordern B, Kwiatkowska R, Majeed A, Priest S, Grimsley J, Lundy L, Singer AC, Di Cesare M. Monitoring occurrence of SARS-CoV-2 in school populations: A wastewater-based approach. PLoS One 2022. [PMID: 35714109 DOI: 10.1101/2021.03.25.21254231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023] Open
Abstract
Clinical testing of children in schools is challenging, with economic implications limiting its frequent use as a monitoring tool of the risks assumed by children and staff during the COVID-19 pandemic. Here, a wastewater-based epidemiology approach has been used to monitor 16 schools (10 primary, 5 secondary and 1 post-16 and further education) in England. A total of 296 samples over 9 weeks have been analysed for N1 and E genes using qPCR methods. Of the samples returned, 47.3% were positive for one or both genes with a detection frequency in line with the respective local community. WBE offers a low cost, non-invasive approach for supplementing clinical testing and can provide longitudinal insights that are impractical with traditional clinical testing.
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Affiliation(s)
- Victor Castro-Gutierrez
- Cranfield University, Bedfordshire, United Kingdom
- Environmental Pollution Research Center (CICA), University of Costa Rica, Montes de Oca, Costa Rica
| | | | - Milan Vu
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Rodrigo Leitao
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Beata Burczynska
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Dirk Wildeboer
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Isobel Stanton
- UK Centre for Ecology and Hydrology, Wallingford, United Kingdom
| | - Shadi Rahimzadeh
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Gianluca Baio
- Department of Statistical Science, University College London, London, United Kingdom
| | - Hemda Garelick
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Jan Hofman
- Water Innovation & Research Centre, Department of Chemical Engineering, University of Bath, Bath, United Kingdom
| | - Barbara Kasprzyk-Hordern
- Water Innovation & Research Centre, Department of Chemistry, University of Bath, Bath, United Kingdom
| | - Rachel Kwiatkowska
- School of Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Field Services, National Infection Service, Public Health England, London, United Kingdom
| | - Azeem Majeed
- Department of Primary Care & Public Health, Imperial College Faculty of Medicine, London, United Kingdom
| | - Sally Priest
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Jasmine Grimsley
- Joint Biosecurity Centre, Department for Health and Social Care, London, United Kingdom
| | - Lian Lundy
- Department of Natural Science, School of Science and Technology, Middlesex University, London, United Kingdom
| | - Andrew C Singer
- UK Centre for Ecology and Hydrology, Wallingford, United Kingdom
| | - Mariachiara Di Cesare
- Institute of Public Health and Wellbeing, University of Essex, Colchester, United Kingdom
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4
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Morrow JB, Packman AI, Martinez KF, Van Den Wymelenberg K, Goeres D, Farmer DK, Mitchell J, Ng L, Hazi Y, Schoch-Spana M, Quinn S, Bahnfleth W, Olsiewski P. Critical Capability Needs for Reduction of Transmission of SARS-CoV-2 Indoors. Front Bioeng Biotechnol 2021; 9:641599. [PMID: 34660544 PMCID: PMC8513777 DOI: 10.3389/fbioe.2021.641599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 04/29/2021] [Indexed: 11/16/2022] Open
Abstract
Coordination of efforts to assess the challenges and pain points felt by industries from around the globe working to reduce COVID-19 transmission in the indoor environment as well as innovative solutions applied to meet these challenges is mandatory. Indoor infectious viral disease transmission (such as coronavirus, norovirus, influenza) is a complex problem that needs better integration of our current knowledge and intervention strategies. Critical to providing a reduction in transmission is to map the four core technical areas of environmental microbiology, transmission science, building science, and social science. To that end a three-stage science and innovation Summit was held to gather information on current standards, policies and procedures applied to reduce transmission in built spaces, as well as the technical challenges, science needs, and research priorities. The Summit elucidated steps than can be taken to reduce transmission of SARS-CoV-2 indoors and calls for significant investments in research to enhance our knowledge of viral pathogen persistence and transport in the built environment, risk assessment and mitigation strategy such as processes and procedures to reduce the risk of exposure and infection through building systems operations, biosurveillance capacity, communication form leadership, and stakeholder engagement for optimal response. These findings reflect the effective application of existing knowledge and standards, emerging science, and lessons-learned from current efforts to confront SARS-CoV-2.
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Affiliation(s)
- Jayne B. Morrow
- Center for Biofilm Engineering, Montana State University, Bozeman, MT, United States
- Integrated Bioscience and Built Environment Consortium (IBEC), Sanford, FL, United States
| | - Aaron I. Packman
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, United States
| | - Kenneth F. Martinez
- Integrated Bioscience and Built Environment Consortium (IBEC), Sanford, FL, United States
- HWC Inc., Washington, DC, United States
| | - Kevin Van Den Wymelenberg
- Biology and the Built Environment Center, College of Design, Institute for Health in the Built Environment, University of Oregon, Eugene, OR, United States
| | - Darla Goeres
- Center for Biofilm Engineering, Montana State University, Bozeman, MT, United States
| | - Delphine K. Farmer
- Department of Chemistry, Colorado State University, Fort Collins, CO, United States
| | - Jade Mitchell
- Department of Biosystems Engineering, Michigan State University, East Lansing, MI, United States
| | - Lisa Ng
- Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, United States
| | - Yair Hazi
- HWC Inc., Washington, DC, United States
| | - Monica Schoch-Spana
- Johns Hopkins Center for Health Security, John Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States
| | - Sandra Quinn
- Department of Family Science and Center for Health Equity, School of Public Health, University of Maryland, College Park, MD, United States
| | - William Bahnfleth
- Department of Architectural Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Paula Olsiewski
- Johns Hopkins Center for Health Security, John Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States
- Alfred P. Sloan Foundation, New York, NY, United States
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5
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Crowe J, Schnaubelt AT, SchmidtBonne S, Angell K, Bai J, Eske T, Nicklin M, Pratt C, White B, Crotts-Hannibal B, Staffend N, Herrera V, Cobb J, Conner J, Carstens J, Tempero J, Bouda L, Ray M, Lawler JV, Campbell WS, Lowe JM, Santarpia J, Bartelt-Hunt S, Wiley M, Brett-Major D, Logan C, Broadhurst MJ. Assessment of a Program for SARS-CoV-2 Screening and Environmental Monitoring in an Urban Public School District. JAMA Netw Open 2021; 4:e2126447. [PMID: 34550382 DOI: 10.1101/2021.04.14.21255036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/26/2023] Open
Abstract
IMPORTANCE Scalable programs for school-based SARS-CoV-2 testing and surveillance are needed to guide in-person learning practices and inform risk assessments in kindergarten through 12th grade settings. OBJECTIVES To characterize SARS-CoV-2 infections in staff and students in an urban public school setting and evaluate test-based strategies to support ongoing risk assessment and mitigation for kindergarten through 12th grade in-person learning. DESIGN, SETTING, AND PARTICIPANTS This pilot quality improvement program engaged 3 schools in Omaha, Nebraska, for weekly saliva polymerase chain reaction testing of staff and students participating in in-person learning over a 5-week period from November 9 to December 11, 2020. Wastewater, air, and surface samples were collected weekly and tested for SARS-CoV-2 RNA to evaluate surrogacy for case detection and interrogate transmission risk of in-building activities. MAIN OUTCOMES AND MEASURES SARS-CoV-2 detection in saliva and environmental samples and risk factors for SARS-CoV-2 infection. RESULTS A total of 2885 supervised, self-collected saliva samples were tested from 458 asymptomatic staff members (mean [SD] age, 42.9 [12.4] years; 303 women [66.2%]; 25 Black or African American [5.5%], 83 Hispanic [18.1%], 312 White [68.1%], and 35 other or not provided [7.6%]) and 315 students (mean age, 14.2 [0.7] years; 151 female students [48%]; 20 Black or African American [6.3%], 201 Hispanic [63.8%], 75 White [23.8%], and 19 other race or not provided [6.0%]). A total of 46 cases of SARS-CoV-2 (22 students and 24 staff members) were detected, representing an increase in cumulative case detection rates from 1.2% (12 of 1000) to 7.0% (70 of 1000) among students and from 2.1% (21 of 1000) to 5.3% (53 of 1000) among staff compared with conventional reporting mechanisms during the pilot period. SARS-CoV-2 RNA was detected in wastewater samples from all pilot schools as well as in air samples collected from 2 choir rooms. Sequencing of 21 viral genomes in saliva specimens demonstrated minimal clustering associated with 1 school. Geographical analysis of SARS-CoV-2 cases reported district-wide demonstrated higher community risk in zip codes proximal to the pilot schools. CONCLUSIONS AND RELEVANCE In this study of staff and students in 3 urban public schools in Omaha, Nebraska, weekly screening of asymptomatic staff and students by saliva polymerase chain reaction testing was associated with increased SARS-CoV-2 case detection, exceeding infection rates reported at the county level. Experiences differed among schools, and virus sequencing and geographical analyses suggested a dynamic interplay of school-based and community-derived transmission risk. Collectively, these findings provide insight into the performance and community value of test-based SARS-CoV-2 screening and surveillance strategies in the kindergarten through 12th grade educational setting.
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Affiliation(s)
- John Crowe
- Omaha Public School District, Omaha, Nebraska
| | - Andy T Schnaubelt
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha
| | | | - Kathleen Angell
- Department of Epidemiology, University of Nebraska Medical Center, Omaha
| | - Julia Bai
- Department of Epidemiology, University of Nebraska Medical Center, Omaha
| | - Teresa Eske
- Omaha Public School District, Omaha, Nebraska
| | | | - Catherine Pratt
- Department of Environmental, Agricultural, and Occupational Health, University of Nebraska Medical Center, Omaha
| | - Bailey White
- Department of Environmental, Agricultural, and Occupational Health, University of Nebraska Medical Center, Omaha
| | | | - Nicholas Staffend
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | - Vicki Herrera
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | | | - Jennifer Conner
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | - Julie Carstens
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | - Jonell Tempero
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | - Lori Bouda
- Omaha Public School District, Omaha, Nebraska
| | - Matthew Ray
- Omaha Public School District, Omaha, Nebraska
| | - James V Lawler
- Department of Medicine, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
| | - W Scott Campbell
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
| | - John-Martin Lowe
- Department of Environmental, Agricultural, and Occupational Health, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
| | - Joshua Santarpia
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
| | | | - Michael Wiley
- Department of Environmental, Agricultural, and Occupational Health, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
| | - David Brett-Major
- Department of Epidemiology, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
| | | | - M Jana Broadhurst
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha
- Global Center for Health Security, University of Nebraska Medical Center, Omaha
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6
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Greenwald HD, Kennedy LC, Hinkle A, Whitney ON, Fan VB, Crits-Christoph A, Harris-Lovett S, Flamholz AI, Al-Shayeb B, Liao LD, Beyers M, Brown D, Chakrabarti AR, Dow J, Frost D, Koekemoer M, Lynch C, Sarkar P, White E, Kantor R, Nelson KL. Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area. WATER RESEARCH X 2021; 12:100111. [PMID: 34373850 DOI: 10.1101/2021.05.04.21256418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/30/2021] [Accepted: 07/25/2021] [Indexed: 05/26/2023]
Abstract
Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility. The concentrations of SARS-CoV-2 in wastewater samples were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall's Tau-b (τ)=0.43 and 0.38, respectively), but no normalization biomarker strengthened the correlation with clinical testing data. Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents tools that could be applied to make wastewater signal more interpretable and comparable across studies.
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Affiliation(s)
- Hannah D Greenwald
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Lauren C Kennedy
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Adrian Hinkle
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Oscar N Whitney
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Vinson B Fan
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Alexander Crits-Christoph
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
| | | | - Avi I Flamholz
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Basem Al-Shayeb
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
| | - Lauren D Liao
- School of Public Health, University of California, Berkeley, CA, USA
| | - Matt Beyers
- Alameda County Public Health Department, San Leandro, CA, USA
| | | | | | - Jason Dow
- Central Marin Sanitation Agency, San Rafael, CA, USA
| | - Dan Frost
- Central Contra Costa Sanitary District, Martinez, CA, USA
| | | | - Chris Lynch
- Contra Costa Health Services, Martinez, CA, USA
| | - Payal Sarkar
- San José-Santa Clara Regional Wastewater Facility, San José, CA, USA
| | - Eileen White
- East Bay Municipal Utility District, Oakland, CA, USA
| | - Rose Kantor
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Kara L Nelson
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
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7
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Greenwald HD, Kennedy LC, Hinkle A, Whitney ON, Fan VB, Crits-Christoph A, Harris-Lovett S, Flamholz AI, Al-Shayeb B, Liao LD, Beyers M, Brown D, Chakrabarti AR, Dow J, Frost D, Koekemoer M, Lynch C, Sarkar P, White E, Kantor R, Nelson KL. Tools for interpretation of wastewater SARS-CoV-2 temporal and spatial trends demonstrated with data collected in the San Francisco Bay Area. WATER RESEARCH X 2021; 12:100111. [PMID: 34373850 PMCID: PMC8325558 DOI: 10.1016/j.wroa.2021.100111] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/30/2021] [Accepted: 07/25/2021] [Indexed: 05/18/2023]
Abstract
Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility. The concentrations of SARS-CoV-2 in wastewater samples were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall's Tau-b (τ)=0.43 and 0.38, respectively), but no normalization biomarker strengthened the correlation with clinical testing data. Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents tools that could be applied to make wastewater signal more interpretable and comparable across studies.
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Affiliation(s)
- Hannah D. Greenwald
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Lauren C. Kennedy
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Adrian Hinkle
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Oscar N. Whitney
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Vinson B. Fan
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Alexander Crits-Christoph
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
| | | | - Avi I. Flamholz
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Basem Al-Shayeb
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
| | - Lauren D. Liao
- School of Public Health, University of California, Berkeley, CA, USA
| | - Matt Beyers
- Alameda County Public Health Department, San Leandro, CA, USA
| | | | | | - Jason Dow
- Central Marin Sanitation Agency, San Rafael, CA, USA
| | - Dan Frost
- Central Contra Costa Sanitary District, Martinez, CA, USA
| | | | - Chris Lynch
- Contra Costa Health Services, Martinez, CA, USA
| | - Payal Sarkar
- San José-Santa Clara Regional Wastewater Facility, San José, CA, USA
| | - Eileen White
- East Bay Municipal Utility District, Oakland, CA, USA
| | - Rose Kantor
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
| | - Kara L. Nelson
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- Berkeley Water Center, University of California, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
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8
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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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