Unraveling a Nosocomial Outbreak of COVID-19: The Role of Whole-Genome Sequence Analysis.

COVID-19 epidemiology nosocomial outbreak sequencing

Journal

Open forum infectious diseases
ISSN: 2328-8957
Titre abrégé: Open Forum Infect Dis
Pays: United States
ID NLM: 101637045

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 15 01 2021
accepted: 09 03 2021
entrez: 11 10 2021
pubmed: 12 10 2021
medline: 12 10 2021
Statut: epublish

Résumé

The coronavirus disease 2019 (COVID-19) pandemic poses many epidemiological challenges. The investigation of nosocomial transmission is usually performed via thorough investigation of an index case and subsequent contact tracing. Notably, this approach has a subjective component, and there is accumulating evidence that whole-genome sequencing of the virus may provide more objective insight. We report a large nosocomial outbreak in 1 of the medicine departments in our institution. Following intensive epidemiological investigation, we discovered that 1 of the patients involved was suffering from persistent COVID-19 while initially thought to be a recovering patient. She was therefore deemed to be the most likely source of the outbreak. We then performed whole-genome sequencing of the virus of 14 infected individuals involved in the outbreak. Surprisingly, the results of whole-genome sequencing refuted our initial hypothesis. A phylogenetic tree of the samples showed multiple introductions of the virus into the ward, 1 of which led to a cluster of 10 of the infected individuals. Importantly, the results pointed in the direction of a specific index patient that was different from the 1 that arose from our initial investigation. These results underscore the important added value of using whole-genome sequencing in epidemiological investigations as it may reveal unexpected connections between cases and aid in understanding transmission dynamics, especially in the setting of a pandemic where multiple possible index cases exist simultaneously.

Sections du résumé

BACKGROUND BACKGROUND
The coronavirus disease 2019 (COVID-19) pandemic poses many epidemiological challenges. The investigation of nosocomial transmission is usually performed via thorough investigation of an index case and subsequent contact tracing. Notably, this approach has a subjective component, and there is accumulating evidence that whole-genome sequencing of the virus may provide more objective insight.
METHODS METHODS
We report a large nosocomial outbreak in 1 of the medicine departments in our institution. Following intensive epidemiological investigation, we discovered that 1 of the patients involved was suffering from persistent COVID-19 while initially thought to be a recovering patient. She was therefore deemed to be the most likely source of the outbreak. We then performed whole-genome sequencing of the virus of 14 infected individuals involved in the outbreak.
RESULTS RESULTS
Surprisingly, the results of whole-genome sequencing refuted our initial hypothesis. A phylogenetic tree of the samples showed multiple introductions of the virus into the ward, 1 of which led to a cluster of 10 of the infected individuals. Importantly, the results pointed in the direction of a specific index patient that was different from the 1 that arose from our initial investigation.
CONCLUSIONS CONCLUSIONS
These results underscore the important added value of using whole-genome sequencing in epidemiological investigations as it may reveal unexpected connections between cases and aid in understanding transmission dynamics, especially in the setting of a pandemic where multiple possible index cases exist simultaneously.

Identifiants

pubmed: 34631912
doi: 10.1093/ofid/ofab120
pii: ofab120
pmc: PMC7989189
doi:

Types de publication

Journal Article

Langues

eng

Pagination

ofab120

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America.

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Auteurs

Suzy E Meijer (SE)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Noam Harel (N)

The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel.
Edmond J. Safra Center for Bioinformatics at Tel Aviv University, Tel Aviv, Israel.

Ronen Ben-Ami (R)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Meital Nahari (M)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Michal Yakubovsky (M)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Howard S Oster (HS)

Department of Internal Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Albert Kolomansky (A)

Department of Internal Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Ora Halutz (O)

Laboratory of Microbiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Orly Laskar (O)

The Department of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, Israel.

Oryan Henig (O)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Adi Stern (A)

The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel.
Edmond J. Safra Center for Bioinformatics at Tel Aviv University, Tel Aviv, Israel.

Yael Paran (Y)

Department of Infectious Diseases and Epidemiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Classifications MeSH