To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
To evaluate the utility of selective reactive whole-genome sequencing (WGS) in aiding healthcare-associated cluster investigations.
Design:
Mixed-methods quality-improvement study.
Setting:
Thes study was conducted across 8 acute-care facilities in an integrated health system.
Methods:
We analyzed healthcare-associated coronavirus disease 2019 (COVID-19) clusters between May 2020 and July 2022 for which facility infection prevention and control (IPC) teams selectively requested reactive WGS to aid the epidemiologic investigation. WGS was performed with real-time results provided to IPC teams, including genetic relatedness of sequenced isolates. We conducted structured interviews with IPC teams on the informativeness of WGS for transmission investigation and prevention.
Results:
In total, 8 IPC teams requested WGS to aid the investigation of 17 COVID-19 clusters comprising 226 cases and 116 (51%) sequenced isolates. Of these, 16 (94%) clusters had at least 1 WGS-defined transmission event. IPC teams hypothesized transmission pathways in 14 (82%) of 17 clusters and used data visualizations to characterize these pathways in 11 clusters (65%). The teams reported that in 15 clusters (88%), WGS identified a transmission pathway; the WGS-defined pathway was not one that was predicted by epidemiologic investigation in 7 clusters (41%). WGS changed the understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in 8 clusters (47%) and altered infection prevention interventions in 8 clusters (47%).
Conclusions:
Selectively utilizing reactive WGS helped identify cryptic SARS-CoV-2 transmission pathways and frequently changed the understanding and response to SARS-CoV-2 outbreaks. Until WGS is widely adopted, a selective reactive WGS approach may be highly impactful in response to healthcare-associated cluster investigations.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.