Nosocomial transmission of influenza: A retrospective cross-sectional study using next generation sequencing at a hospital in England (2012-2014)
Author(s)
Type
Journal Article
Abstract
Background
The extent of transmission of influenza in hospital settings is poorly understood. Next generation sequencing may improve this by providing information on the genetic relatedness of viral strains.
Objectives
We aimed to apply next generation sequencing to describe transmission in hospital and compare with methods based on routinely‐collected data.
Methods
All influenza samples taken through routine care from patients at University College London Hospitals NHS Foundation Trust (September 2012 to March 2014) were included. We conducted Illumina sequencing and identified genetic clusters. We compared nosocomial transmission estimates defined using classical methods (based on time from admission to sample) and genetic clustering. We identified pairs of cases with space‐time links and assessed genetic relatedness.
Results
We sequenced influenza sampled from 214 patients. There were 180 unique genetic strains, 16 (8.8%) of which seeded a new transmission chain. Nosocomial transmission was indicated for 32 (15.0%) cases using the classical definition and 34 (15.8%) based on genetic clustering. Of the 50 patients in a genetic cluster, 11 (22.0%) had known space‐time links with other cases in the same cluster. Genetic distances between pairs of cases with space‐time links were lower than for pairs without spatial links (P < .001).
Conclusions
Genetic data confirmed that nosocomial transmission contributes significantly to the hospital burden of influenza and elucidated transmission chains. Prospective next generation sequencing could support outbreak investigations and monitor the impact of infection and control measures.
The extent of transmission of influenza in hospital settings is poorly understood. Next generation sequencing may improve this by providing information on the genetic relatedness of viral strains.
Objectives
We aimed to apply next generation sequencing to describe transmission in hospital and compare with methods based on routinely‐collected data.
Methods
All influenza samples taken through routine care from patients at University College London Hospitals NHS Foundation Trust (September 2012 to March 2014) were included. We conducted Illumina sequencing and identified genetic clusters. We compared nosocomial transmission estimates defined using classical methods (based on time from admission to sample) and genetic clustering. We identified pairs of cases with space‐time links and assessed genetic relatedness.
Results
We sequenced influenza sampled from 214 patients. There were 180 unique genetic strains, 16 (8.8%) of which seeded a new transmission chain. Nosocomial transmission was indicated for 32 (15.0%) cases using the classical definition and 34 (15.8%) based on genetic clustering. Of the 50 patients in a genetic cluster, 11 (22.0%) had known space‐time links with other cases in the same cluster. Genetic distances between pairs of cases with space‐time links were lower than for pairs without spatial links (P < .001).
Conclusions
Genetic data confirmed that nosocomial transmission contributes significantly to the hospital burden of influenza and elucidated transmission chains. Prospective next generation sequencing could support outbreak investigations and monitor the impact of infection and control measures.
Date Issued
2019-11
Date Acceptance
2019-08-25
Citation
Influenza and Other Respiratory Viruses, 2019, 13 (6), pp.556-563
ISSN
1750-2640
Publisher
Wiley Open Access
Start Page
556
End Page
563
Journal / Book Title
Influenza and Other Respiratory Viruses
Volume
13
Issue
6
Copyright Statement
© 2019 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000486820000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Infectious Diseases
Virology
cross infection
disease outbreaks
influenza
human
molecular epidemiology
SEASONAL INFLUENZA
H1N1 VIRUS
HEMAGGLUTININ
INFECTIONS
OUTBREAKS
Publication Status
Published
Date Publish Online
2019-09-19