Clinical perspectives in integrating whole-genome sequencing into the investigation of healthcare and public health outbreaks – hype or help?

B. J. Parcell, S. H. Gillespie, K. A. Pettigrew, M. T.G. Holden

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
1 Downloads (Pure)

Abstract

Outbreaks pose a significant risk to patient safety as well as being costly and time consuming to investigate. The implementation of targeted infection prevention and control measures relies on infection prevention and control teams having access to rapid results that detect resistance accurately, and typing results that give clinically useful information on the relatedness of isolates. At present, determining whether transmission has occurred can be a major challenge. Conventional typing results do not always have sufficient granularity or robustness to define strains unequivocally, and sufficient epidemiological data are not always available to establish links between patients and the environment. Whole-genome sequencing (WGS) has emerged as the ultimate genotyping tool, but has not yet fully crossed the divide between research method and routine clinical diagnostic microbiological technique. A clinical WGS service was officially established in 2014 as part of the Scottish Healthcare Associated Infection Prevention Institute to confirm or refute outbreaks in hospital settings from across Scotland. This article describes the authors' experiences with the aim of providing new insights into practical application of the use of WGS to investigate healthcare and public health outbreaks. Solutions to overcome barriers to implementation of this technology in a clinical environment are proposed.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalJournal of Hospital Infection
Volume109
Early online date9 Nov 2020
DOIs
Publication statusPublished - 1 Mar 2021
Externally publishedYes

Bibliographical note

Funding Information:
Bioinformatics and Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit, which is funded by a Wellcome Trust ISSF award (Grant 097831/Z/11/Z). The Scottish Healthcare Associated Infection Prevention Institute Consortium is funded by the Chief Scientist Office through the Scottish Infection Research Network (SIRN10).

Funding Information:
Bioinformatics and Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit, which is funded by a Wellcome Trust ISSF award (Grant 097831/Z/11/Z ). The Scottish Healthcare Associated Infection Prevention Institute Consortium is funded by the Chief Scientist Office through the Scottish Infection Research Network ( SIRN10 ).

Publisher Copyright:
© 2020 The Authors

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