1
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Amirali A, Babler KM, Sharkey ME, Beaver CC, Boone MM, Comerford S, Cooper D, Currall BB, Goodman KW, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Mason CE, Reding BD, Roca MA, Ryon K, Schürer SC, Shukla BS, Solle NS, Stevenson M, Tallon JJ, Vidović D, Williams SL, Yin X, Solo-Gabriele HM. Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus. Sci Total Environ 2024; 918:170452. [PMID: 38296085 PMCID: PMC10923133 DOI: 10.1016/j.scitotenv.2024.170452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/30/2023] [Accepted: 01/19/2024] [Indexed: 02/07/2024]
Abstract
Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses.
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Affiliation(s)
- Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Cynthia C Beaver
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Melinda M Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samuel Comerford
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | | | - Benjamin B Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Kenneth W Goodman
- Frost Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA; Institute for Bioethics and Health Policy, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter E Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146, USA
| | - Bhavarth S Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA
| | - Natasha Schaefer Solle
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Mario Stevenson
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dušica Vidović
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Xue Yin
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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2
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Zhan Q, Solo-Gabriele HM, Sharkey ME, Amirali A, Beaver CC, Boone MM, Comerford S, Cooper D, Cortizas EM, Cosculluela GA, Currall BB, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Lyu J, Mason CE, Reding BD, Roca MA, Schürer SC, Shukla BS, Solle NS, Suarez MM, Stevenson M, Tallon JJ, Thomas C, Vidović D, Williams SL, Yin X, Zarnegarnia Y, Babler KM. Correlative analysis of wastewater trends with clinical cases and hospitalizations through five dominant variant waves of COVID-19. ACS ES T Water 2023; 3:2849-2862. [PMID: 38487696 PMCID: PMC10936583 DOI: 10.1021/acsestwater.3c00032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
Wastewater-based epidemiology (WBE) has been utilized to track community infections of Coronavirus Disease 2019 (COVID-19) by detecting RNA of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), within samples collected from wastewater. The correlations between community infections and wastewater measurements of the RNA can potentially change as SARS-CoV-2 evolves into new variations by mutating. This study analyzed SARS-CoV-2 RNA, and indicators of human waste in wastewater from two sewersheds of different scales (University of Miami (UM) campus and Miami-Dade County Central District wastewater treatment plant (CDWWTP)) during five internally defined COVID-19 variant dominant periods (Initial, Pre-Delta, Delta, Omicron and Post-Omicron wave). SARS-CoV-2 RNA quantities were compared against COVID-19 clinical cases and hospitalizations to evaluate correlations with wastewater SARS-CoV-2 RNA. Although correlations between documented clinical cases and hospitalizations were high, prevalence for a given wastewater SARS-CoV-2 level varied depending upon the variant analyzed. The correlative relationship was significantly steeper (more cases per level found in wastewater) for the Omicron-dominated period. For hospitalization, the relationships were steepest for the Initial wave, followed by the Delta wave with flatter slopes during all other waves. Overall results were interpreted in the context of SARS-CoV-2 virulence and vaccination rates among the community.
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Affiliation(s)
- Qingyu Zhan
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Helena Maria Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Mark E. Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Cynthia C. Beaver
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Samuel Comerford
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
| | | | - Elena M. Cortizas
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Gabriella A. Cosculluela
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Benjamin B. Currall
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - George S. Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136 USA
| | - Walter E. Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136 USA
| | - Jiangnan Lyu
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021 USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Brian D. Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136 USA
| | - Matthew A. Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Stephan C. Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL 33136 USA
- Institute for Data Science & Computing, University of Miami, Coral Gables, FL 33146 USA
| | - Bhavarth S. Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
| | - Natasha Schaefer Solle
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Maritza M. Suarez
- Department of Medicine, University of Miami Miller School of Medicine, Miami, 33136 FL USA
| | - Mario Stevenson
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - John J. Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146 USA
| | - Collette Thomas
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Dušica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL 33136 USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Xue Yin
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
| | - Yalda Zarnegarnia
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Kristina Marie Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146 USA
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3
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Tierney BT, Foox J, Ryon KA, Butler D, Damle N, Young BG, Mozsary C, Babler KM, Yin X, Carattini Y, Andrews D, Solle NS, Kumar N, Shukla B, Vidovic D, Currall B, Williams SL, Schürer SC, Stevenson M, Amirali A, Beaver CC, Kobetz E, Boone MM, Reding B, Laine J, Comerford S, Lamar WE, Tallon JJ, Hirschberg JW, Proszynski J, Sharkey ME, Church GM, Grills GS, Solo-Gabriele HM, Mason CE. Geospatially-resolved public-health surveillance via wastewater sequencing. medRxiv 2023:2023.05.31.23290781. [PMID: 37398062 PMCID: PMC10312847 DOI: 10.1101/2023.05.31.23290781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Wastewater, which contains everything from pathogens to pollutants, is a geospatially-and temporally-linked microbial fingerprint of a given population. As a result, it can be leveraged for monitoring multiple dimensions of public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (n=1,419 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County from 2020-2022. First, we used targeted amplicon sequencing (n=966) to track diverse SARS-CoV-2 variants across space and time, and we found a tight correspondence with clinical caseloads from University students (N = 1,503) and Miami-Dade County hospital patients (N = 3,939 patients), as well as an 8-day earlier detection of the Delta variant in wastewater vs. in patients. Additionally, in 453 metatranscriptomic samples, we demonstrate that different wastewater sampling locations have clinically and public-health-relevant microbiota that vary as a function of the size of the human population they represent. Through assembly, alignment-based, and phylogenetic approaches, we also detect multiple clinically important viruses (e.g., norovirus ) and describe geospatial and temporal variation in microbial functional genes that indicate the presence of pollutants. Moreover, we found distinct profiles of antimicrobial resistance (AMR) genes and virulence factors across campus buildings, dorms, and hospitals, with hospital wastewater containing a significant increase in AMR abundance. Overall, this effort lays the groundwork for systematic characterization of wastewater to improve public health decision making and a broad platform to detect emerging pathogens.
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4
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Babler KM, Sharkey ME, Abelson S, Amirali A, Benitez A, Cosculluela GA, Grills GS, Kumar N, Laine J, Lamar W, Lamm ED, Lyu J, Mason CE, McCabe PM, Raghavender J, Reding BD, Roca MA, Schürer SC, Stevenson M, Szeto A, Tallon JJ, Vidović D, Zarnegarnia Y, Solo-Gabriele HM. Degradation rates influence the ability of composite samples to represent 24-hourly means of SARS-CoV-2 and other microbiological target measures in wastewater. Sci Total Environ 2023; 867:161423. [PMID: 36623667 PMCID: PMC9817413 DOI: 10.1016/j.scitotenv.2023.161423] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The utility of using severe-acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA for assessing the prevalence of COVID-19 within communities begins with the design of the sample collection program. The objective of this study was to assess the utility of 24-hour composites as representative samples for measuring multiple microbiological targets in wastewater, and whether normalization of SARS-CoV-2 by endogenous targets can be used to decrease hour to hour variability at different watershed scales. Two sets of experiments were conducted, in tandem with the same wastewater, with samples collected at the building, cluster, and community sewershed scales. The first set of experiments focused on evaluating degradation of microbiological targets: SARS-CoV-2, Simian Immunodeficiency Virus (SIV) - a surrogate spiked into the wastewater, plus human waste indicators of Pepper Mild Mottle Virus (PMMoV), Beta-2 microglobulin (B2M), and fecal coliform bacteria (FC). The second focused on the variability of these targets from samples, collected each hour on the hour. Results show that SARS-CoV-2, PMMoV, and B2M were relatively stable, with minimal degradation over 24-h. SIV, which was spiked-in prior to analysis, degraded significantly and FC increased significantly over the course of 24 h, emphasizing the possibility for decay and growth within wastewater. Hour-to-hour variability of the source wastewater was large between each hour of sampling relative to the variability of the SARS-CoV-2 levels calculated between sewershed scales; thus, differences in SARS-CoV-2 hourly variability were not statistically significant between sewershed scales. Results further provided that the quantified representativeness of 24-h composite samples (i.e., statistical equivalency compared against hourly collected grabs) was dependent upon the molecular target measured. Overall, improvements made by normalization were minimal within this study. Degradation and multiplication for other targets should be evaluated when deciding upon whether to collect composite or grab samples in future studies.
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Affiliation(s)
- Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Aymara Benitez
- Miami-Dade Water and Sewer Department, Miami, FL 33149, USA
| | - Gabriella A Cosculluela
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Walter Lamar
- Division of Occupational Health, Safety & Compliance, University of Miami Health System, Miami, FL 33136, USA
| | - Erik D Lamm
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Jiangnan Lyu
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10021, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY 10021, USA
| | - Philip M McCabe
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA; Department of Biomedical Engineering, University of Miami, Coral Gables, FL 33146, USA
| | | | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL 33136, USA
| | - Matthew A Roca
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Angela Szeto
- Department of Psychology, University of Miami, Coral Gables, FL 33146, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL 33146, USA
| | - Dusica Vidović
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Yalda Zarnegarnia
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL 33146, USA.
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5
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Solo-Gabriele HM, Kumar S, Abelson S, Penso J, Contreras J, Babler KM, Sharkey ME, Mantero AMA, Lamar WE, Tallon JJ, Kobetz E, Solle NS, Shukla BS, Kenney RJ, Mason CE, Schürer SC, Vidovic D, Williams SL, Grills GS, Jayaweera DT, Mirsaeidi M, Kumar N. Predicting COVID-19 cases using SARS-CoV-2 RNA in air, surface swab and wastewater samples. Sci Total Environ 2023; 857:159188. [PMID: 36202365 PMCID: PMC9529341 DOI: 10.1016/j.scitotenv.2022.159188] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/11/2022] [Accepted: 09/29/2022] [Indexed: 05/08/2023]
Abstract
Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples, which can serve as a noninvasive method of infectious disease surveillance. The research evaluates the efficacy of environmental monitoring of SARS-CoV-2 RNA in air, surface swabs and wastewater to predict COVID-19 cases. Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory housing roughly 500 students from March to May 2021 at the University of Miami, Coral Gables, FL. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 concentration in environmental samples was quantified using Volcano 2nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and COVID-19 cases. SARS-CoV-2 was detected in air, surface swab and wastewater samples on 52 (63.4 %), 40 (50.0 %) and 57 (68.6 %) days, respectively. On 19 (24 %) of 78 days SARS-CoV-2 was detected in all three sample types. COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100 %), 9 (81.8 %) and 8 (72.7 %) days in air, surface swab and wastewater samples, respectively. SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases and a 3-day lead indicator for a potential outbreak at the dormitory building scale. Proactive environmental surveillance of SARS-CoV-2 or other pathogens in multiple environmental media has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks within communities.
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Affiliation(s)
- Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami, Coral Gables, FL, United States of America
| | - Shelja Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Johnathon Penso
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Julio Contreras
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami, Coral Gables, FL, United States of America
| | - Mark E Sharkey
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Alejandro M A Mantero
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America
| | - Walter E Lamar
- Facilities Safety & Compliance, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL, United States of America
| | - Erin Kobetz
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Natasha Schaefer Solle
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Bhavarth S Shukla
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Richard J Kenney
- Department of Housing & Residential Life, University of Miami, Coral Gables, FL, United States of America
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, United States of America
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, United States of America; Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - George S Grills
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Dushyantha T Jayaweera
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Mehdi Mirsaeidi
- Division of Pulmonary, Critical Care and Sleep, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL, United States of America
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, United States of America.
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6
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Solo-Gabriele HM, Kumar S, Abelson S, Penso J, Contreras J, Babler KM, Sharkey ME, Mantero AMA, Lamar WE, Tallon JJ, Kobetz E, Solle NS, Shukla BS, Kenney RJ, Mason CE, Schürer SC, Vidovic D, Williams SL, Grills GS, Jayaweera DT, Mirsaeidi M, Kumar N. COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples. medRxiv 2022:2022.03.14.22272314. [PMID: 35313580 PMCID: PMC8936103 DOI: 10.1101/2022.03.14.22272314] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Importance Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples. Analysis of these samples can be employed for noninvasive surveillance of infectious diseases. Objective To evaluate the efficacy of environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for predicting COVID-19 cases in a college dormitory. Design Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory from March to May 2021. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases. Setting This study was conducted in a residential dormitory at the University of Miami, Coral Gables campus, FL, USA. The dormitory housed about 500 students. Participants Students from the dormitory were randomly screened, for COVID-19 for 2-3 days / week while entering or exiting the dormitory. Main Outcome Clinically diagnosed COVID-19 cases were of our main interest. We hypothesized that SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases in the dormitory, and SARS-CoV-2 can be detected in the environmental samples several days prior to the clinical diagnosis of COVID-19 cases. Results SARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively. Conclusion Proactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks. Key Points Question: How effective is environmental surveillance of SARS-CoV-2 in public places for early detection of COVID-19 cases in a community?Findings: All clinically confirmed COVID-19 cases were predicted with the aid of 2 day lagged SARS-CoV-2 in environmental samples in a college dormitory. However, the prediction efficiency varied by sample type: best prediction by air samples, followed by wastewater and surface swab samples. SARS-CoV-2 was also detected in these samples even on days without any reported cases of COVID-19, suggesting underreporting of COVID-19 cases.Meaning: SARS-CoV-2 can be detected in environmental samples several days prior to clinical reporting of COVID-19 cases. Thus, proactive environmental surveillance of microbiome in public places can serve as a mean for early detection of location-time specific outbreaks of infectious diseases. It can also be used for underreporting of infectious diseases.
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Affiliation(s)
- Helena M. Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami; Coral Gables FL
| | - Shelja Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
| | - Samantha Abelson
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
| | - Johnathon Penso
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
| | - Julio Contreras
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
| | - Kristina M. Babler
- Department of Chemical, Environmental, and Materials Engineering, College of Engineering, University of Miami; Coral Gables FL
| | - Mark E. Sharkey
- Department of Medicine, Miller School of Medicine, University of Miami; Miami FL
| | - Alejandro M. A. Mantero
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
| | - Walter E. Lamar
- Facilities Safety & Compliance, Miller School of Medicine, University of Miami; Miami FL
| | - John J. Tallon
- Facilities and Operations, University of Miami; Coral Gables FL
| | - Erin Kobetz
- Department of Medicine, Miller School of Medicine, University of Miami; Miami FL
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami; Miami FL
| | - Natasha Schaefer Solle
- Department of Medicine, Miller School of Medicine, University of Miami; Miami FL
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami; Miami FL
| | - Bhavarth S. Shukla
- Department of Medicine, Miller School of Medicine, University of Miami; Miami FL
| | - Richard J. Kenney
- Department of Housing & Residential Life, University of Miami; Coral Gables FL
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College; New York City NY
| | - Stephan C. Schürer
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami; Miami FL
- Institute for Data Science & Computing, University of Miami; Coral Gables FL
- Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami; Miami FL
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, Miller School of Medicine, University of Miami; Miami FL
| | - Sion L. Williams
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami; Miami FL
| | - George S. Grills
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami; Miami FL
| | | | - Mehdi Mirsaeidi
- Division of Pulmonary, Critical Care and Sleep, College of Medicine-Jacksonville University of Florida, Jacksonville FL
| | - Naresh Kumar
- Department of Public Health Sciences, Miller School of Medicine, University of Miami; Miami FL 33136
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Sharkey ME, Kumar N, Mantero AMA, Babler KM, Boone MM, Cardentey Y, Cortizas EM, Grills GS, Herrin J, Kemper JM, Kenney R, Kobetz E, Laine J, Lamar WE, Mader CC, Mason CE, Quintero AZ, Reding BD, Roca MA, Ryon K, Solle NS, Schürer SC, Shukla B, Stevenson M, Stone T, Tallon JJ, Venkatapuram SS, Vidovic D, Williams SL, Young B, Solo-Gabriele HM. Lessons learned from SARS-CoV-2 measurements in wastewater. Sci Total Environ 2021; 798:149177. [PMID: 34375259 PMCID: PMC8294117 DOI: 10.1016/j.scitotenv.2021.149177] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 07/16/2021] [Accepted: 07/17/2021] [Indexed: 05/02/2023]
Abstract
Standardized protocols for wastewater-based surveillance (WBS) for the RNA of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, are being developed and refined worldwide for early detection of disease outbreaks. We report here on lessons learned from establishing a WBS program for SARS-CoV-2 integrated with a human surveillance program for COVID-19. We have established WBS at three campuses of a university, including student residential dormitories and a hospital that treats COVID-19 patients. Lessons learned from this WBS program address the variability of water quality, new detection technologies, the range of detectable viral loads in wastewater, and the predictive value of integrating environmental and human surveillance data. Data from our WBS program indicated that water quality was statistically different between sewer sampling sites, with more variability observed in wastewater coming from individual buildings compared to clusters of buildings. A new detection technology was developed based upon the use of a novel polymerase called V2G. Detectable levels of SARS-CoV-2 in wastewater varied from 102 to 106 genomic copies (gc) per liter of raw wastewater (L). Integration of environmental and human surveillance data indicate that WBS detection of 100 gc/L of SARS-CoV-2 RNA in wastewater was associated with a positivity rate of 4% as detected by human surveillance in the wastewater catchment area, though confidence intervals were wide (β ~ 8.99 ∗ ln(100); 95% CI = 0.90-17.08; p < 0.05). Our data also suggest that early detection of COVID-19 surges based on correlations between viral load in wastewater and human disease incidence could benefit by increasing the wastewater sample collection frequency from weekly to daily. Coupling simpler and faster detection technology with more frequent sampling has the potential to improve the predictive potential of using WBS of SARS-CoV-2 for early detection of the onset of COVID-19.
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Affiliation(s)
- Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alejandro M A Mantero
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kristina M Babler
- Department of Marine Biology and Ecology, University of Miami, Key Biscayne, FL, USA
| | - Melinda M Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Yoslayma Cardentey
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Elena M Cortizas
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - George S Grills
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Jenny M Kemper
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Richard Kenney
- Housing Operations & Facilities, University of Miami, Coral Gables, FL, USA
| | - Erin Kobetz
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Walter E Lamar
- Facilities Safety & Compliance, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Christopher C Mader
- Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, USA
| | | | - Brian D Reding
- Environmental Health and Safety, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Matthew A Roca
- Department of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, FL, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, USA
| | - Natasha Schaefer Solle
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Institute for Data Science & Computing, University of Miami, Coral Gables, FL, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, USA
| | - Bhavarth Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Mario Stevenson
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Thomas Stone
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - John J Tallon
- Facilities and Operations, University of Miami, Coral Gables, FL, USA
| | | | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, USA
| | - Sion L Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Benjamin Young
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, USA
| | - Helena M Solo-Gabriele
- Department of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, FL, USA.
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