Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmissionCitation formats

  • External authors:
  • Jamie M Ellingford
  • Ryan George
  • John H Mcdermott
  • Shazaad Ahmad
  • Jonathan J Edgerley
  • David Gokhale
  • Stephen Ball
  • Nicholas Machin

Standard

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.

In: eLife, Vol. 10, e65453, 17.03.2021.

Research output: Contribution to journalArticlepeer-review

Harvard

Ellingford, JM, George, R, Mcdermott, JH, Ahmad, S, Edgerley, JJ, Gokhale, D, Newman, WG, Ball, S, Machin, N & Black, GC 2021, 'Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission', eLife, vol. 10, e65453. https://doi.org/10.7554/eLife.65453

APA

Ellingford, J. M., George, R., Mcdermott, J. H., Ahmad, S., Edgerley, J. J., Gokhale, D., Newman, W. G., Ball, S., Machin, N., & Black, G. C. (2021). Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission. eLife, 10, [e65453]. https://doi.org/10.7554/eLife.65453

Vancouver

Ellingford JM, George R, Mcdermott JH, Ahmad S, Edgerley JJ, Gokhale D et al. Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission. eLife. 2021 Mar 17;10. e65453. https://doi.org/10.7554/eLife.65453

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. / Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission. In: eLife. 2021 ; Vol. 10.

Bibtex

@article{436e7275bb15418ea77fc996b4cfc777,
title = "Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission",
abstract = "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.",
author = "Ellingford, {Jamie M} and Ryan George and Mcdermott, {John H} and Shazaad Ahmad and Edgerley, {Jonathan J} and David Gokhale and Newman, {William G} and Stephen Ball and Nicholas Machin and Black, {Graeme Cm}",
year = "2021",
month = mar,
day = "17",
doi = "10.7554/eLife.65453",
language = "English",
volume = "10",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",

}

RIS

TY - JOUR

T1 - Genomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission

AU - Ellingford, Jamie M

AU - George, Ryan

AU - Mcdermott, John H

AU - Ahmad, Shazaad

AU - Edgerley, Jonathan J

AU - Gokhale, David

AU - Newman, William G

AU - Ball, Stephen

AU - Machin, Nicholas

AU - Black, Graeme Cm

PY - 2021/3/17

Y1 - 2021/3/17

N2 - 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.

AB - 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.

U2 - 10.7554/eLife.65453

DO - 10.7554/eLife.65453

M3 - Article

VL - 10

JO - eLife

JF - eLife

SN - 2050-084X

M1 - e65453

ER -