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Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?

BACKGROUND: Epidemiologic investigations are foundational in outbreak evaluations but are unable to fully capture the innumerable interactions that lead to exposure. Whole Genome Sequencing (WGS) offers clonality information that can suggest potential transmission links but is costly and resource in...

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Autores principales: Olenslager, Keith, Yim, Jennifer, Dickey, Linda, Bueno, Emily, Tifrea, Delia F., Crumpler, Megan, Huang, Susan, Gohil, Shruti K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Mosby, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9215285/
http://dx.doi.org/10.1016/j.ajic.2022.03.114
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author Olenslager, Keith
Yim, Jennifer
Dickey, Linda
Bueno, Emily
Tifrea, Delia F.
Crumpler, Megan
Huang, Susan
Gohil, Shruti K.
author_facet Olenslager, Keith
Yim, Jennifer
Dickey, Linda
Bueno, Emily
Tifrea, Delia F.
Crumpler, Megan
Huang, Susan
Gohil, Shruti K.
author_sort Olenslager, Keith
collection PubMed
description BACKGROUND: Epidemiologic investigations are foundational in outbreak evaluations but are unable to fully capture the innumerable interactions that lead to exposure. Whole Genome Sequencing (WGS) offers clonality information that can suggest potential transmission links but is costly and resource intensive. We compared COVID-19 exposure source as determined by contact tracing investigations with linkages inferred by WGS data for a COVID-19 outbreak among healthcare workers (HCWs) and patients. METHODS: Contact tracing investigations were conducted for HCWs identified in three COVID-19 hospital clusters and included interviews to assess exposure history and infection prevention breaches and categorized as either: Community, HCW-to-HCW, Patient-to-HCW, HCW-to-Patient, or Unknown. WGS evaluations were completed for 45 (34 HCWs,11 patients) COVID-19 positive samples (Quiagen EZ1 RNA extraction, Illumina Nextera FLex library/Illumina NextSeq 500). Exposure source determinations were reevaluated using WGS data. Agreement between the two strategies were described as percentage and compared using Cohen's Kappa. RESULTS: Among 45 samples submitted, 37 were successfully sequenced, and19 (51%,17 HCWs and 2 patients) were identified as potentially linked clonal Epsilon (B.1.429) COVID-19 variant strains. WGS identified 13 identical and 6 closely related strains that suggested linkages between 15 HCW-HCW, 2 HCW-Patient, 1 community, and 1 unknown transmission. Contact tracing categorized the 19 cases as: 8 HCW-HCW, 1 Patient-HCW, 3 Community, and 7 Unknown. After incorporating WGS data, these were reclassified as 9 HCW-HCW, 5 Community, and 5 Unknown. Combining contact tracing with WGS information resulted in 6 (32%) reclassifications; agreement between the two strategies was 58% (Cohen's kappa=0.19), identifying 1 previously unrecognized 1 HCW-HCW and 2 community cases. While contact tracing had suggested 1 patient-HCW transmission, WGS results did not show matching strains. CONCLUSIONS: WGS can improve the precision of COVID-19 outbreak investigation of transmission links in almost one third of cases.
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spelling pubmed-92152852022-06-22 Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing? Olenslager, Keith Yim, Jennifer Dickey, Linda Bueno, Emily Tifrea, Delia F. Crumpler, Megan Huang, Susan Gohil, Shruti K. Am J Infect Control Its-67 BACKGROUND: Epidemiologic investigations are foundational in outbreak evaluations but are unable to fully capture the innumerable interactions that lead to exposure. Whole Genome Sequencing (WGS) offers clonality information that can suggest potential transmission links but is costly and resource intensive. We compared COVID-19 exposure source as determined by contact tracing investigations with linkages inferred by WGS data for a COVID-19 outbreak among healthcare workers (HCWs) and patients. METHODS: Contact tracing investigations were conducted for HCWs identified in three COVID-19 hospital clusters and included interviews to assess exposure history and infection prevention breaches and categorized as either: Community, HCW-to-HCW, Patient-to-HCW, HCW-to-Patient, or Unknown. WGS evaluations were completed for 45 (34 HCWs,11 patients) COVID-19 positive samples (Quiagen EZ1 RNA extraction, Illumina Nextera FLex library/Illumina NextSeq 500). Exposure source determinations were reevaluated using WGS data. Agreement between the two strategies were described as percentage and compared using Cohen's Kappa. RESULTS: Among 45 samples submitted, 37 were successfully sequenced, and19 (51%,17 HCWs and 2 patients) were identified as potentially linked clonal Epsilon (B.1.429) COVID-19 variant strains. WGS identified 13 identical and 6 closely related strains that suggested linkages between 15 HCW-HCW, 2 HCW-Patient, 1 community, and 1 unknown transmission. Contact tracing categorized the 19 cases as: 8 HCW-HCW, 1 Patient-HCW, 3 Community, and 7 Unknown. After incorporating WGS data, these were reclassified as 9 HCW-HCW, 5 Community, and 5 Unknown. Combining contact tracing with WGS information resulted in 6 (32%) reclassifications; agreement between the two strategies was 58% (Cohen's kappa=0.19), identifying 1 previously unrecognized 1 HCW-HCW and 2 community cases. While contact tracing had suggested 1 patient-HCW transmission, WGS results did not show matching strains. CONCLUSIONS: WGS can improve the precision of COVID-19 outbreak investigation of transmission links in almost one third of cases. Published by Mosby, Inc. 2022-07 2022-06-22 /pmc/articles/PMC9215285/ http://dx.doi.org/10.1016/j.ajic.2022.03.114 Text en Copyright © 2022 Published by Mosby, Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Its-67
Olenslager, Keith
Yim, Jennifer
Dickey, Linda
Bueno, Emily
Tifrea, Delia F.
Crumpler, Megan
Huang, Susan
Gohil, Shruti K.
Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title_full Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title_fullStr Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title_full_unstemmed Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title_short Whole Genome Sequencing (WGS) for COVID-19 Outbreak Evaluations – How Much Does It Add to Bootstrap Epidemiology & Contact Tracing?
title_sort whole genome sequencing (wgs) for covid-19 outbreak evaluations – how much does it add to bootstrap epidemiology & contact tracing?
topic Its-67
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9215285/
http://dx.doi.org/10.1016/j.ajic.2022.03.114
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