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COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples
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 respir...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936103/ https://www.ncbi.nlm.nih.gov/pubmed/35313580 http://dx.doi.org/10.1101/2022.03.14.22272314 |
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author | Solo-Gabriele, Helena M. Kumar, Shelja Abelson, Samantha Penso, Johnathon Contreras, Julio Babler, Kristina M. Sharkey, Mark E. Mantero, Alejandro M. A. Lamar, Walter E. Tallon, John J. Kobetz, Erin Solle, Natasha Schaefer Shukla, Bhavarth S. Kenney, Richard J. Mason, Christopher E. Schürer, Stephan C. Vidovic, Dusica Williams, Sion L. Grills, George S. Jayaweera, Dushyantha T. Mirsaeidi, Mehdi Kumar, Naresh |
author_facet | Solo-Gabriele, Helena M. Kumar, Shelja Abelson, Samantha Penso, Johnathon Contreras, Julio Babler, Kristina M. Sharkey, Mark E. Mantero, Alejandro M. A. Lamar, Walter E. Tallon, John J. Kobetz, Erin Solle, Natasha Schaefer Shukla, Bhavarth S. Kenney, Richard J. Mason, Christopher E. Schürer, Stephan C. Vidovic, Dusica Williams, Sion L. Grills, George S. Jayaweera, Dushyantha T. Mirsaeidi, Mehdi Kumar, Naresh |
author_sort | Solo-Gabriele, Helena M. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8936103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-89361032022-03-22 COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples Solo-Gabriele, Helena M. Kumar, Shelja Abelson, Samantha Penso, Johnathon Contreras, Julio Babler, Kristina M. Sharkey, Mark E. Mantero, Alejandro M. A. Lamar, Walter E. Tallon, John J. Kobetz, Erin Solle, Natasha Schaefer Shukla, Bhavarth S. Kenney, Richard J. Mason, Christopher E. Schürer, Stephan C. Vidovic, Dusica Williams, Sion L. Grills, George S. Jayaweera, Dushyantha T. Mirsaeidi, Mehdi Kumar, Naresh medRxiv Article 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. Cold Spring Harbor Laboratory 2022-04-01 /pmc/articles/PMC8936103/ /pubmed/35313580 http://dx.doi.org/10.1101/2022.03.14.22272314 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Solo-Gabriele, Helena M. Kumar, Shelja Abelson, Samantha Penso, Johnathon Contreras, Julio Babler, Kristina M. Sharkey, Mark E. Mantero, Alejandro M. A. Lamar, Walter E. Tallon, John J. Kobetz, Erin Solle, Natasha Schaefer Shukla, Bhavarth S. Kenney, Richard J. Mason, Christopher E. Schürer, Stephan C. Vidovic, Dusica Williams, Sion L. Grills, George S. Jayaweera, Dushyantha T. Mirsaeidi, Mehdi Kumar, Naresh COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title | COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title_full | COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title_fullStr | COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title_full_unstemmed | COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title_short | COVID-19 Prediction using Genomic Footprint of SARS-CoV-2 in Air, Surface Swab and Wastewater Samples |
title_sort | covid-19 prediction using genomic footprint of sars-cov-2 in air, surface swab and wastewater samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936103/ https://www.ncbi.nlm.nih.gov/pubmed/35313580 http://dx.doi.org/10.1101/2022.03.14.22272314 |
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