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Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission
Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009659/ https://www.ncbi.nlm.nih.gov/pubmed/33729154 http://dx.doi.org/10.7554/eLife.65453 |
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author | Ellingford, Jamie M George, Ryan McDermott, John H Ahmad, Shazaad Edgerley, Jonathan J Gokhale, David Newman, William G Ball, Stephen Machin, Nicholas Black, Graeme CM |
author_facet | Ellingford, Jamie M George, Ryan McDermott, John H Ahmad, Shazaad Edgerley, Jonathan J Gokhale, David Newman, William G Ball, Stephen Machin, Nicholas Black, Graeme CM |
author_sort | Ellingford, Jamie M |
collection | PubMed |
description | Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting. |
format | Online Article Text |
id | pubmed-8009659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-80096592021-03-31 Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission Ellingford, Jamie M George, Ryan McDermott, John H Ahmad, Shazaad Edgerley, Jonathan J Gokhale, David Newman, William G Ball, Stephen Machin, Nicholas Black, Graeme CM eLife Genetics and Genomics Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting. eLife Sciences Publications, Ltd 2021-03-17 /pmc/articles/PMC8009659/ /pubmed/33729154 http://dx.doi.org/10.7554/eLife.65453 Text en © 2021, Ellingford et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Genetics and Genomics Ellingford, Jamie M George, Ryan McDermott, John H Ahmad, Shazaad Edgerley, Jonathan J Gokhale, David Newman, William G Ball, Stephen Machin, Nicholas Black, Graeme CM Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title | Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title_full | Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title_fullStr | Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title_full_unstemmed | Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title_short | Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission |
title_sort | genomic and healthcare dynamics of nosocomial sars-cov-2 transmission |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009659/ https://www.ncbi.nlm.nih.gov/pubmed/33729154 http://dx.doi.org/10.7554/eLife.65453 |
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