151
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Brooks YM, Gryskwicz B, Sheehan S, Piers S, Mahale P, McNeil S, Chase J, Webber D, Borys D, Hilton M, Robinson D, Sears S, Smith E, Lesher EK, Wilson R, Goodwin M, Pardales M. Detection of SARS-CoV-2 in Wastewater at Residential College, Maine, USA, August-November 2020. Emerg Infect Dis 2021; 27:3111-3114. [PMID: 34465415 PMCID: PMC8632168 DOI: 10.3201/eid2712.211199] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
We used wastewater surveillance to identify 2 coronavirus disease outbreaks at a college in Maine, USA. Cumulative increases of >1 log10 severe acute respiratory syndrome coronavirus 2 RNA in consecutive 24-hour composite samples preceded the outbreaks. For 76% of cases, RNA was identified in grab samples from residence halls <7 days before case discovery.
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152
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McClary-Gutierrez JS, Mattioli MC, Marcenac P, Silverman AI, Boehm AB, Bibby K, Balliet M, de Los Reyes FL, Gerrity D, Griffith JF, Holden PA, Katehis D, Kester G, LaCross N, Lipp EK, Meiman J, Noble RT, Brossard D, McLellan SL. SARS-CoV-2 Wastewater Surveillance for Public Health Action. Emerg Infect Dis 2021. [PMID: 34424162 DOI: 10.20944/preprints202104.0167.v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023] Open
Abstract
Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.
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153
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Scott LC, Aubee A, Babahaji L, Vigil K, Tims S, Aw TG. Targeted wastewater surveillance of SARS-CoV-2 on a university campus for COVID-19 outbreak detection and mitigation. ENVIRONMENTAL RESEARCH 2021; 200:111374. [PMID: 34058182 PMCID: PMC8163699 DOI: 10.1016/j.envres.2021.111374] [Citation(s) in RCA: 104] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/23/2021] [Accepted: 05/19/2021] [Indexed: 05/17/2023]
Abstract
Targeted wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been proposed by the United States Centers for Disease Control and Prevention's National Wastewater Surveillance System as a complementary approach to clinical surveillance to detect the presence of Coronavirus Disease 2019 (COVID-19) at high-density facilities and institutions such as university campuses, nursing homes, and correctional facilities. In this study we evaluated the efficacy of targeted wastewater surveillance of SARS-CoV-2 RNA together with individual-level testing for outbreak mitigation on a university campus during Fall 2020 semester. Wastewater samples (n = 117) were collected weekly from manholes or sewer cleanouts that receive wastewater inputs from dormitories, community-use buildings, and a COVID-19 isolation dormitory. Quantitative RT-PCR N1 and N2 assays were used to measure SARS-CoV-2 nucleocapsid genes in wastewater. Due to varying human waste input in different buildings, pepper mild mottle virus (PMMV) RNA was also measured in all samples and used to normalize SARS-CoV-2 N1 and N2 RNA wastewater concentrations. In this study, temporal trends of SARS-CoV-2 in wastewater samples mirrored trends in COVID-19 cases detected on campus. Normalizing SARS-CoV-2 RNA concentrations using human fecal indicator, PMMV enhanced the correlation between N1 and N2 gene abundances in wastewater with COVID-19 cases. N1 and N2 genes were significant predictors of COVID-19 cases in dormitories, and the N2 gene was significantly correlated with the number of detected COVID-19 cases in dormitories. By implementing several public health surveillance programs include targeted wastewater surveillance, individual-level testing, contact tracing, and quarantine/isolation facilities, university health administrators could act decisively during an outbreak on campus, resulting in rapid decline of newly detected COVID-19 cases. Wastewater surveillance of SARS-CoV-2 is a proactive outbreak monitoring tool for university campuses seeking to continue higher education practices in person during the COVID-19 pandemic.
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Affiliation(s)
- Laura C Scott
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Alexandra Aubee
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Layla Babahaji
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Katie Vigil
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Scott Tims
- Campus Health and Student Services, Tulane University, New Orleans, LA, USA
| | - Tiong Gim Aw
- Department of Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
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154
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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. [PMID: 34550382 DOI: 10.1101/2021.04.14.21255036v1%0a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] 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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155
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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 PMCID: PMC8459193 DOI: 10.1001/jamanetworkopen.2021.26447] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/27/2021] [Indexed: 02/01/2023] 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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156
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Wu F, Xiao A, Zhang J, Moniz K, Endo N, Armas F, Bushman M, Chai PR, Duvallet C, Erickson TB, Foppe K, Ghaeli N, Gu X, Hanage WP, Huang KH, Lee WL, McElroy KA, Rhode SF, Matus M, Wuertz S, Thompson J, Alm EJ. Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020. WATER RESEARCH 2021; 202:117400. [PMID: 34274898 PMCID: PMC8249441 DOI: 10.1016/j.watres.2021.117400] [Citation(s) in RCA: 97] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/11/2021] [Accepted: 06/28/2021] [Indexed: 05/18/2023]
Abstract
Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.
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Affiliation(s)
- Fuqing Wu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Amy Xiao
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jianbo Zhang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Katya Moniz
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, 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
| | - Mary Bushman
- Harvard T.H. Chan School of Public Health, Harvard University, 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
| | | | - Timothy B Erickson
- Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, USA; The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, USA; Harvard Humanitarian Initiative, Harvard University
| | | | | | - 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
| | | | - Steven F Rhode
- Massachusetts Water Resources Authority, Boston, MA, USA
| | | | - Stefan Wuertz
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - 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, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, 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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157
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McClary-Gutierrez JS, Mattioli MC, Marcenac P, Silverman AI, Boehm AB, Bibby K, Balliet M, de Los Reyes FL, Gerrity D, Griffith JF, Holden PA, Katehis D, Kester G, LaCross N, Lipp EK, Meiman J, Noble RT, Brossard D, McLellan SL. SARS-CoV-2 Wastewater Surveillance for Public Health Action. Emerg Infect Dis 2021; 27:1-8. [PMID: 34424162 PMCID: PMC8386792 DOI: 10.3201/eid2709.210753] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.
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158
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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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159
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Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus. mSystems 2021; 6:e0079321. [PMID: 34374562 PMCID: PMC8409724 DOI: 10.1128/msystems.00793-21] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Wastewater-based surveillance has gained prominence and come to the forefront as a leading indicator of forecasting COVID-19 (coronavirus disease 2019) infection dynamics owing to its cost-effectiveness and its ability to inform early public health interventions. A university campus could especially benefit from wastewater surveillance, as universities are characterized by largely asymptomatic populations and are potential hot spots for transmission that necessitate frequent diagnostic testing. In this study, we employed a large-scale GIS (geographic information systems)-enabled building-level wastewater monitoring system associated with the on-campus residences of 7,614 individuals. Sixty-eight automated wastewater samplers were deployed to monitor 239 campus buildings with a focus on residential buildings. Time-weighted composite samples were collected on a daily basis and analyzed on the same day. Sample processing was streamlined significantly through automation, reducing the turnaround time by 20-fold and exceeding the scale of similar surveillance programs by 10- to 100-fold, thereby overcoming one of the biggest bottlenecks in wastewater surveillance. An automated wastewater notification system was developed to alert residents to a positive wastewater sample associated with their residence and to encourage uptake of campus-provided asymptomatic testing at no charge. This system, integrated with the rest of the "Return to Learn" program at the University of California (UC) San Diego-led to the early diagnosis of nearly 85% of all COVID-19 cases on campus. COVID-19 testing rates increased by 1.9 to 13× following wastewater notifications. Our study shows the potential for a robust, efficient wastewater surveillance system to greatly reduce infection risk as college campuses and other high-risk environments reopen. IMPORTANCE Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks. The highly automated sample processing to reporting system enabled dramatic reduction in the turnaround time to 5 h (sample to result time) for 96 samples. Furthermore, miniaturization of the sample processing pipeline brought down the processing cost significantly ($13/sample). Taken together, these results show that such a system could greatly ameliorate long-term surveillance on such communities as they look to reopen.
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160
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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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161
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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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162
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Acosta N, Bautista MA, Hollman J, McCalder J, Beaudet AB, Man L, Waddell BJ, Chen J, Li C, Kuzma D, Bhatnagar S, Leal J, Meddings J, Hu J, Cabaj JL, Ruecker NJ, Naugler C, Pillai DR, Achari G, Ryan MC, Conly JM, Frankowski K, Hubert CR, Parkins MD. A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks. WATER RESEARCH 2021; 201:117369. [PMID: 34229222 PMCID: PMC8214445 DOI: 10.1016/j.watres.2021.117369] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/07/2021] [Accepted: 06/12/2021] [Indexed: 05/18/2023]
Abstract
SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.
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Affiliation(s)
- Nicole Acosta
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation
| | - María A Bautista
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Jordan Hollman
- Department of Geosciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation; Department of Civil Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Janine McCalder
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation; Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Alexander Buchner Beaudet
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Lawrence Man
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Barbara J Waddell
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation
| | - Jianwei Chen
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Carmen Li
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Darina Kuzma
- Advancing Canadian Wastewater Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta, Abbreviation
| | - Srijak Bhatnagar
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Jenine Leal
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation; Infection Prevention and Control, Alberta Health Services, 1403 29th Street NW, Calgary, Alberta, Abbreviation; Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Abbreviation; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta, Abbreviation
| | - Jon Meddings
- Department of Medicine, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation
| | - Jia Hu
- Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Abbreviation; Provincial Population & Public Health, Alberta Health Services, 3030 Hospital Drive NW, Calgary, Alberta, Abbreviation; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta, Abbreviation
| | - Jason L Cabaj
- Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Abbreviation; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta, Abbreviation
| | - Norma J Ruecker
- Water Quality Services, City of Calgary, 625 25 Ave SE, Calgary, Alberta, Abbreviation
| | - Christopher Naugler
- Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, Alberta, Abbreviation; Department of Pathology and Laboratory Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation
| | - Dylan R Pillai
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation; Department of Pathology and Laboratory Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation; Alberta Precision Laboratories, Alberta Health Services, 3535 Research Rd NW, Calgary, Alberta, Abbreviation
| | - Gopal Achari
- Department of Civil Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - M Cathryn Ryan
- Department of Geosciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - John M Conly
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation; Infection Prevention and Control, Alberta Health Services, 1403 29th Street NW, Calgary, Alberta, Abbreviation; Department of Medicine, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation; O'Brien Institute for Public Health, University of Calgary, 3280 Hospital Dr NW, Calgary, Alberta, Abbreviation; Department of Pathology and Laboratory Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation; Snyder Institute for Chronic Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation
| | - Kevin Frankowski
- Advancing Canadian Wastewater Assets, University of Calgary, 3131 210 Ave SE, Calgary, Alberta, Abbreviation
| | - Casey Rj Hubert
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Abbreviation
| | - Michael D Parkins
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, Abbreviation; Department of Medicine, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation; Snyder Institute for Chronic Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Abbreviation.
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163
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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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164
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Harris-Lovett S, Nelson KL, Beamer P, Bischel HN, Bivins A, Bruder A, Butler C, Camenisch TD, De Long SK, Karthikeyan S, Larsen DA, Meierdiercks K, Mouser PJ, Pagsuyoin S, Prasek SM, Radniecki TS, Ram JL, Roper DK, Safford H, Sherchan SP, Shuster W, Stalder T, Wheeler RT, Korfmacher KS. Wastewater Surveillance for SARS-CoV-2 on College Campuses: Initial Efforts, Lessons Learned, and Research Needs. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:4455. [PMID: 33922263 PMCID: PMC8122720 DOI: 10.3390/ijerph18094455] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/15/2021] [Accepted: 04/17/2021] [Indexed: 01/28/2023]
Abstract
Wastewater surveillance for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging approach to help identify the risk of a coronavirus disease (COVID-19) outbreak. This tool can contribute to public health surveillance at both community (wastewater treatment system) and institutional (e.g., colleges, prisons, and nursing homes) scales. This paper explores the successes, challenges, and lessons learned from initial wastewater surveillance efforts at colleges and university systems to inform future research, development and implementation. We present the experiences of 25 college and university systems in the United States that monitored campus wastewater for SARS-CoV-2 during the fall 2020 academic period. We describe the broad range of approaches, findings, resources, and impacts from these initial efforts. These institutions range in size, social and political geographies, and include both public and private institutions. Our analysis suggests that wastewater monitoring at colleges requires consideration of local information needs, sewage infrastructure, resources for sampling and analysis, college and community dynamics, approaches to interpretation and communication of results, and follow-up actions. Most colleges reported that a learning process of experimentation, evaluation, and adaptation was key to progress. This process requires ongoing collaboration among diverse stakeholders including decision-makers, researchers, faculty, facilities staff, students, and community members.
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Affiliation(s)
- Sasha Harris-Lovett
- Berkeley Water Center, University of California Berkeley, 410 O’Brien Hall, Berkeley, CA 94720, USA
| | - Kara L. Nelson
- Department of Civil and Environmental Engineering, University of California Berkeley, MS 1710, Berkeley, CA 94720, USA;
| | - Paloma Beamer
- Department of Community, Environment & Policy, Zuckerman College of Public Health, University of Arizona, 1295 N Martin Ave., Tucson, AZ 85724, USA;
| | - Heather N. Bischel
- Department of Civil and Environmental Engineering, University of California Davis, 3109 Ghausi Hall, One Shields Ave., Davis, CA 95616, USA;
| | - Aaron Bivins
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, USA;
| | - Andrea Bruder
- Department of Mathematics and Computer Science, Colorado College, 14 E Cache la Poudre St., Colorado Springs, CO 80903, USA;
| | - Caitlyn Butler
- Department of Civil and Environmental Engineering, University of Massachusetts Amherst, 130 Natural Resources Rd., Amherst, MA 01003, USA;
| | - Todd D. Camenisch
- Department of Pharmaceutical Sciences, St. John Fisher College, 3690 East Ave., Rochester, NY 14618, USA;
| | - Susan K. De Long
- Department of Civil and Environmental Engineering, 1301 Campus Delivery, Colorado State University, Fort Collins, CO 80526, USA;
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California San Diego, Biomedical Res. Facility 2, 9500 Gilman Drive, La Jolla, CA 92037, USA;
| | - David A. Larsen
- Department of Public Health, Syracuse University, 430C Barclay, Syracuse, New York, NY 13244, USA;
| | - Katherine Meierdiercks
- Department of Environmental Studies and Sciences, Siena College, 515 Loudon Rd., Loudonville, NY 12211, USA;
| | - Paula J. Mouser
- Department of Civil and Environmental Engineering, University of New Hampshire Durham, 35 Colovos Rd., 236 Gregg Hall, Durham, NH 03824, USA;
| | - Sheree Pagsuyoin
- Department of Civil and Environmental Engineering, University of Massachusetts Lowell, 1 University Avenue, Lowell, MA 01854, USA;
| | - Sarah M. Prasek
- Water and Energy Sustainable Technology Center, University of Arizona, 2959 W Calle Agua Nueva, Tucson, AZ 85745, USA;
| | - Tyler S. Radniecki
- School of Chemical, Biological, and Environmental Engineering, Oregon State University, 116 Johnson Hall, 105 SW 26th St., Corvallis, OR 97331, USA;
| | - Jeffrey L. Ram
- Department of Physiology, Wayne State University, 540 E. Canfield St., Detroit, MI 48201, USA;
| | - D. Keith Roper
- Department of Biological Engineering, Utah State University, 4105 Old Main Hill, Logan, UT 84322, USA;
| | - Hannah Safford
- Department of Civil and Environmental Engineering, University of California Davis, 2001 Ghausi Hall, 480 Bainer Hall Drive, Davis, CA 95616, USA;
| | - Samendra P. Sherchan
- Department of Environmental Health Science, Tulane University, 1440 Canal St., New Orleans, LA 70112, USA;
| | - William Shuster
- Department of Civil and Environmental Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA;
| | - Thibault Stalder
- Department of Biological Sciences, University of Idaho, 875 Perimeter Dr. MS3051, Moscow, ID 83844, USA;
| | - Robert T. Wheeler
- Department of Molecular and Biomedical Sciences, University of Maine, 5735 Hitchner Hall, Orono, ME 04473, USA;
| | - Katrina Smith Korfmacher
- Department of Environmental Medicine, University of Rochester, 601 Elmwood Ave., Box EHSC, Rochester, NY 14642, USA;
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Brooks YM, Gryskwicz B, Sheehan S, Piers S, Mahale P, McNeil S, Chase J, Webber D, Borys D, Hilton M, Robinson D, Sears S, Smith E, Lesher EK, Wilson R, Goodwin M, Pardales M. Detection of SARS-CoV-2 in Wastewater at Residential College, Maine, USA, August-November 2020. Emerg Infect Dis 2021. [PMID: 34465415 DOI: 10.3201/eid2712.21119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023] Open
Abstract
We used wastewater surveillance to identify 2 coronavirus disease outbreaks at a college in Maine, USA. Cumulative increases of >1 log10 severe acute respiratory syndrome coronavirus 2 RNA in consecutive 24-hour composite samples preceded the outbreaks. For 76% of cases, RNA was identified in grab samples from residence halls <7 days before case discovery.
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Sharara N, Endo N, Duvallet C, Ghaeli N, Matus M, Heussner J, Olesen SW, Alm EJ, Chai PR, Erickson TB. Wastewater network infrastructure in public health: Applications and learnings from the COVID-19 pandemic. PLOS GLOBAL PUBLIC HEALTH 2021; 1:e0000061. [PMID: 34927170 PMCID: PMC8682811 DOI: 10.1371/journal.pgph.0000061] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Accurate estimates of COVID-19 burden of infections in communities can inform public health strategy for the current pandemic. Wastewater based epidemiology (WBE) leverages sewer infrastructure to provide insights on rates of infection by measuring viral concentrations in wastewater. By accessing the sewer network at various junctures, important insights regarding COVID-19 disease activity can be gained. The analysis of sewage at the wastewater treatment plant level enables population-level surveillance of disease trends and virus mutations. At the neighborhood level, WBE can be used to describe trends in infection rates in the community thereby facilitating local efforts at targeted disease mitigation. Finally, at the building level, WBE can suggest the presence of infections and prompt individual testing. In this critical review, we describe the types of data that can be obtained through varying levels of WBE analysis, concrete plans for implementation, and public health actions that can be taken based on WBE surveillance data of infectious diseases, using recent and successful applications of WBE during the COVID-19 pandemic for illustration.
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Affiliation(s)
- Nour Sharara
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
- * E-mail: (TBE); (NS)
| | - Noriko Endo
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Claire Duvallet
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Newsha Ghaeli
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Mariana Matus
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Jennings Heussner
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Scott W. Olesen
- Biobot Analytics, Inc., Cambridge, Massachusetts, United States of America
| | - Eric J. Alm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore, Singapore
- Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Peter R. Chai
- Division of Medical Toxicology, Department of Emergency Medicine, Mass General Brigham, Harvard Medical School, Boston, Massachusetts, United States of America
- The Fenway Institute, Boston, Massachusetts, United States of America
- The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Division of Psychosocial Oncology and Palliative Care, Dana Farber Cancer Institute, Boston, Massachusetts, United States of America
| | - Timothy B. Erickson
- Division of Medical Toxicology, Department of Emergency Medicine, Mass General Brigham, Harvard Medical School, Boston, Massachusetts, United States of America
- Harvard Humanitarian Initiative, Cambridge, Massachusetts, United States of America
- * E-mail: (TBE); (NS)
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