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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2022
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.
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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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