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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Goldstein SA, Feeley TM, Babler KM, Hilbert ZA, Downhour DM, Moshiri N, Elde NC. Hidden evolutionary constraints dictate the retention of coronavirus accessory genes. bioRxiv 2024:2023.10.12.561935. [PMID: 37873270 PMCID: PMC10592793 DOI: 10.1101/2023.10.12.561935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Coronaviruses exhibit many mechanisms of genetic innovation (1-5), including the acquisition of accessory genes that originate by capture of cellular genes or through duplication of existing viral genes (6,7). Accessory genes influence viral host range and cellular tropism, but little is known about how selection acts on these variable regions of virus genomes. We used experimental evolution of mouse hepatitis virus (MHV) encoding a cellular AKAP7 phosphodiesterase and an inactive native phosphodiesterase, NS2 (ref 8) to simulate the capture of a host gene and analyze its evolution. After courses of serial infection, the gene encoding inactive NS2, ORF2, unexpectedly remained intact, suggesting it is under cryptic constraint uncoupled from the function of NS2. In contrast, AKAP7 was retained under strong selection but rapidly lost under relaxed selection. Guided by the retention of ORF2 and similar patterns in related betacoronaviruses, we analyzed ORF8 of SARS-CoV-2, which arose via gene duplication6 and contains premature stop codons in several globally successful lineages. As with MHV ORF2, the coding-defective SARS-CoV-2 ORF8 gene remains largely intact, mirroring patterns observed during MHV experimental evolution, challenging assumptions on the dynamics of gene loss in virus genomes and extending these findings to viruses currently adapting to humans.
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3
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Babler KM, Sharkey ME, Amirali A, Boone MM, Comerford S, Currall BB, Grills GS, Laine J, Mason CE, Reding B, Schürer S, Stevenson M, Vidović D, Williams SL, Solo-Gabriele HM. Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification. J Biomol Tech 2023; 34:3fc1f5fe.dfa8d906. [PMID: 38268997 PMCID: PMC10805363 DOI: 10.7171/3fc1f5fe.dfa8d906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment.
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Affiliation(s)
- Kristina M. Babler
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
| | - Mark E. Sharkey
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Ayaaz Amirali
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Samuel Comerford
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Benjamin B. Currall
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - George S. Grills
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Jennifer Laine
- Environmental Health and SafetyUniversity of MiamiMiamiFlorida33136USA
| | - Christopher E. Mason
- Department of Physiology and BiophysicsWeill Cornell
MedicineNew YorkNew York10065USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud
Institute for Computational BiomedicineWeill Cornell MedicineNew
YorkNew York10065USA
- The WorldQuant Initiative for Quantitative PredictionWeill Cornell MedicineNew YorkNew YorkUSA 10065USA
| | - Brian Reding
- Environmental Health and SafetyUniversity of MiamiMiamiFlorida33136USA
| | - Stephan Schürer
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
- Department of Molecular and Cellular PharmacologyUniversity of Miami Miller School of MedicineMiamiFlorida33136USA
- Institute for Data Science & Computing, University of
MiamiCoral GablesFlorida33146USA
| | - Mario Stevenson
- Department of MedicineUniversity of Miami Miller School
of MedicineMiamiFlorida33136USA
| | - Dušica Vidović
- Department of Molecular and Cellular PharmacologyUniversity of Miami Miller School of MedicineMiamiFlorida33136USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer CenterUniversity of Miami
Miller School of MedicineMiamiFlorida33136USA
| | - Helena M. Solo-Gabriele
- Department of ChemicalEnvironmental and Materials
EngineeringUniversity of MiamiCoral GablesFlorida33124USA
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4
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Sharkey ME, Babler KM, Shukla BS, Abelson SM, Alsuliman B, Amirali A, Comerford S, Grills GS, Kumar N, Laine J, Lee J, Lamar WE, Mason CE, Penso J, Reding BD, Schürer SC, Stevenson M, Vidović D, Solo-Gabriele HM. Monkeypox viral nucleic acids detected using both DNA and RNA extraction workflows. Sci Total Environ 2023; 890:164289. [PMID: 37216988 PMCID: PMC10213602 DOI: 10.1016/j.scitotenv.2023.164289] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [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: 03/29/2023] [Revised: 05/15/2023] [Accepted: 05/15/2023] [Indexed: 05/24/2023]
Abstract
Molecular methods have been used to detect human pathogens in wastewater with sampling typically performed at wastewater treatment plants (WWTP) and upstream locations within the sewer system. A wastewater-based surveillance (WBS) program was established at the University of Miami (UM) in 2020, which included measurements of SARS-CoV-2 levels in wastewater from its hospital and within the regional WWTP. In addition to the development of a SARS-CoV-2 quantitative PCR (qPCR) assay, qPCR assays to detect other human pathogens of interest were also developed at UM. Here we report on the use of a modified set of reagents published by the CDC to detect nucleic acids of Monkeypox virus (MPXV) which emerged during May of 2022 to become a concern worldwide. Samples collected from the University hospital and from the regional WWTP were processed through DNA and RNA workflows and analyzed by qPCR to detect a segment of the MPXV CrmB gene. Results show positive detections of MPXV nucleic acids in the hospital and wastewater treatment plant wastewater which coincided with clinical cases in the community and mirrored the overall trend of nationwide MPXV cases reported to the CDC. We recommend the expansion of current WBS programs' methods to detect a broader range of pathogens of concern in wastewater and present evidence that viral RNA in human cells infected by a DNA virus can be detected in wastewater.
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Affiliation(s)
- Mark E Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kristina M Babler
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Bhavarth S Shukla
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Samantha M Abelson
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Bader Alsuliman
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA
| | - Samuel Comerford
- Department of Medicine, 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
| | - Naresh Kumar
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jennifer Laine
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Jisue Lee
- University of Miami Health System, Miami, FL, USA
| | - Walter E Lamar
- Facilities Safety & Compliance, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY, USA
| | - Johnathon Penso
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Brian D Reding
- Environmental Health and Safety, University of Miami, Miami, FL, USA
| | - Stephan C Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, 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, USA
| | - Dušica Vidović
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL, USA
| | - Helena M Solo-Gabriele
- Department of Chemical, Environmental, and Materials Engineering, University of Miami, Coral Gables, FL, USA.
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5
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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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6
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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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7
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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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8
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Babler KM, Amirali A, Sharkey ME, Williams SL, Boone MM, Cosculluela GA, Currall BB, Grills GS, Laine J, Mason CE, Reding BD, Schürer SC, Stevenson M, Vidovic D, Solo-Gabriele HM. Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater. ACS ES T Water 2022; 2:2004-2013. [PMID: 37601294 PMCID: PMC10438908 DOI: 10.1021/acsestwater.2c00047] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.
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Affiliation(s)
- Kristina M. Babler
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Ayaaz Amirali
- Department of Chemical, Environmental and Materials Engineering, Coral Gables, FL USA
| | - Mark E. Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL USA
| | - Sion L. Williams
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | - Melinda M. Boone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
| | | | - Benjamin B. Currall
- 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
| | - Jennifer Laine
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY USA
| | | | - Brian D. Reding
- Department of Physiology and Biophysics and the WorldQuant Initiative, Weill Cornell Medicine, New York City, NY USA
| | - Stephan C. Schürer
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL USA
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL 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 USA
| | - Dusica Vidovic
- Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, FL USA
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9
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Zhan Q, Babler KM, Sharkey ME, Amirali A, Beaver CC, Boone MM, Comerford S, Cooper D, Cortizas EM, Currall BB, Foox J, Grills GS, Kobetz E, Kumar N, Laine J, Lamar WE, Mantero AM, Mason CE, Reding BD, Robertson M, Roca MA, Ryon K, Schürer SC, Shukla BS, Solle NS, Stevenson M, Tallon Jr JJ, Thomas C, Thomas T, Vidović D, Williams SL, Yin X, Solo-Gabriele HM. Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste. ACS ES T Water 2022; 2:1992-2003. [PMID: 36398131 PMCID: PMC9664448 DOI: 10.1021/acsestwater.2c00045] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.
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Affiliation(s)
- Qingyu Zhan
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Kristina M. Babler
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Mark E. Sharkey
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Ayaaz Amirali
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Cynthia C. Beaver
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Melinda M. Boone
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Samuel Comerford
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Daniel Cooper
- DataGrade
Solutions, LLC, Miami, Florida 33173, United
States
| | - Elena M. Cortizas
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Benjamin B. Currall
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Jonathan Foox
- Department
of Physiology and Biophysics, Weill Cornell
Medical College, New York
City, New York 10021, United States
| | - George S. Grills
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Erin Kobetz
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Naresh Kumar
- Department
of Public Health Sciences, University of
Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Jennifer Laine
- Environmental
Health and Safety, University of Miami, Miami, Florida 33146, United States
| | - Walter E. Lamar
- Facilities
Safety & Compliance, University of Miami
Miller School of Medicine, Miami, Florida 33136, United States
| | - Alejandro M.A. Mantero
- Department
of Public Health Sciences, University of
Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Christopher E. Mason
- Department
of Physiology and Biophysics and the WorldQuant Initiative for Quantitative
Prediction, Weill Cornell Medical College, New York City, New York 10021, United States
| | - Brian D. Reding
- Environmental
Health and Safety, University of Miami, Miami, Florida 33146, United States
| | - Maria Robertson
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Matthew A. Roca
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Krista Ryon
- Department
of Physiology and Biophysics, Weill Cornell
Medical College, New York
City, New York 10021, United States
| | - Stephan C. Schürer
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
- Department
of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, Florida 33136, United States
- Institute
for Data Science & Computing, University
of Miami, Coral Gables, Florida 33146, United
States
| | - Bhavarth S. Shukla
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - Natasha Schaefer Solle
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Mario Stevenson
- Department
of Medicine, University of Miami Miller
School of Medicine, Miami, Florida 33136, United States
| | - John J. Tallon Jr
- Facilities
and Operations, University of Miami, Coral Gables, Florida 33146, United States
| | - Collette Thomas
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Tori Thomas
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Dušica Vidović
- Department
of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicines, Miami, Florida 33136, United States
| | - Sion L. Williams
- Sylvester
Comprehensive Cancer Center, University
of Miami Miller School of Medicine, Miami, Florida 33136, United States
| | - Xue Yin
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
| | - Helena M. Solo-Gabriele
- Department
of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida 33146, United States
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10
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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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11
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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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12
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Mozsary C, McCloskey D, Babler KM, Boza J, Butler D, Currall B, Williams S, Wiley A, Afshin EE, Grills GS, Sharkey ME, Premsrirut P, Solo-Gabriele H, Cardentey Y, Erickson D, Mason CE. A Rapid, Isothermal, and Point-of-Care System for COVID-19 Diagnostics. J Biomol Tech 2021; 32:221-227. [PMID: 35136383 PMCID: PMC8802758 DOI: 10.7171/jbt.21-3203-019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The COVID-19 pandemic has had a profound, detrimental effect on economies and societies worldwide. Where the pandemic has been controlled, extremely high rates of diagnostic testing for the SARS-CoV-2 virus have proven critical, enabling isolation of cases and contact tracing. Recently, diagnostic testing has been supplemented with wastewater measures to evaluate the degree to which communities have infections. Whereas much testing has been done through traditional, centralized, clinical, or environmental laboratory methods, point-of-care testing has proven successful in reducing time to result. As the pandemic progresses and becomes more broadly distributed, further decentralization of diagnostic testing will be helpful to mitigate its spread. This will be particularly both challenging and critical in settings with limited resources due to lack of medical infrastructure and expertise as well as requirements to return results quickly. In this article, we validate the tiny isothermal nucleic acid quantification system (TINY) and a novel loop-mediated isothermal amplification (LAMP)-based assay for the point-of-care diagnosis of SARS-CoV-2 infection in humans and also for in-the-field, point-of-collection surveillance of wastewater. The TINY system is portable and designed for use in settings with limited resources. It can be powered by electrical, solar, or thermal energy and is robust against interruptions in services. These applied testing examples demonstrate that this novel detection platform is a simpler procedure than reverse-transcription quantitative polymerase chain reaction, and moreover, this TINY instrument and LAMP assay combination has the potential to effectively provide both point-of-care diagnosis of individuals and point-of-collection environmental surveillance using wastewater.
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Affiliation(s)
- Christopher Mozsary
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA
| | - Duncan McCloskey
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Kristina M. Babler
- Department of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida, USA
| | - Juan Boza
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Daniel Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA
| | - Benjamin Currall
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA
| | - Sion Williams
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA
| | - Anne Wiley
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | - Evan E. Afshin
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA
| | - George S. Grills
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA
| | - Mark E. Sharkey
- Department of Medicine, University of Miami Miller School of Medicine, Miami, Florida USA
| | | | - Helena Solo-Gabriele
- Department of Civil, Architectural, and Environmental Engineering, University of Miami, Coral Gables, Florida, USA
| | - Yoslayma Cardentey
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA
| | - David Erickson
- Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA
- Division of Nutritional Sciences, Cornell University, Ithaca, New York, USA
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA
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