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Factors contributing to a coronavirus disease 2019 (COVID-19) outbreak on a mixed medical-surgical unit in a Canadian acute-care hospital.
McCallum, Megan K; Patriquin, Glenn; Davis, Ian R C; MacDonald, Tammy; Gaston, Daniel; LeBlanc, Jason J; Shabi, Yahya; Johnston, B Lynn.
Affiliation
  • McCallum MK; Infection Prevention and Control, Nova Scotia Health, Halifax, Nova Scotia, Canada.
  • Patriquin G; Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada.
  • Davis IRC; Department of Pathology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.
  • MacDonald T; Department of Medicine, Nova Scotia Health and Department of Medicine, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Gaston D; Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada.
  • LeBlanc JJ; Department of Pathology, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Shabi Y; Department of Medicine, Nova Scotia Health and Department of Medicine, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.
  • Johnston BL; Infection Prevention and Control, Nova Scotia Health, Halifax, Nova Scotia, Canada.
Article in En | MEDLINE | ID: mdl-36483428
ABSTRACT

Objective:

To identify preventable factors that contribute to the cross transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) to patients in healthcare facilities.

Design:

A case-control study was conducted among inpatients on a coronavirus disease 2019 (COVID-19) outbreak unit.

Setting:

This study was conducted in a medical-surgical unit of a tertiary-care hospital in Nova Scotia in May 2021. Patients Patients hospitalized on the unit for at least 12 hours and healthcare workers (HCW) working on the unit within 2 weeks of outbreak declaration were included.

Methods:

Risk factors for SARS-CoV-2 infection were analyzed using simple and multiple logistic regression. Whole-genome sequencing (WGS) was performed to identify SARS-CoV-2 strain relatedness. Network analysis was used to describe patient accommodation.

Results:

SARS-CoV-2 infections were identified in 21 patients (29.6%) and 11 HCWs (6.6%). WGS data revealed 4 distinct clades of related sequences. Several factors likely contributed to the outbreak, including failure to identify SARS-CoV-2, a largely incomplete or unvaccinated population, and patient wandering behaviors. The most significant risk factor for SARS-CoV-2 infection was room sharing with an infectious patient, which was the only factor that remained statistically significant following multivariate analysis (odds ratio [OR], 9.2l; 95% confidence interval [CI], 2.04-41.67; P = .004).

Conclusions:

This outbreak likely resulted from admission of 2 patients with COVID-19, with subsequent transmissions to 17 patients and 11 staff. WGS and bioinformatics analyses were critical to identifying previously unrecognized nosocomial transmissions of SARS-CoV-2. This study supports strategies to reduce nosocomial transmissions of SARS-CoV-2, such as single-patient rooms, promotion of COVID-19 vaccination, and infection prevention and control measures including management of wandering behaviors.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Antimicrob Steward Healthc Epidemiol Year: 2022 Document type: Article Affiliation country: Canadá

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Antimicrob Steward Healthc Epidemiol Year: 2022 Document type: Article Affiliation country: Canadá