Stirrup, Oliver, Hughes, Joseph, Parker, Matthew, Partridge, David G, Shepherd, James G, Blackstone, James, Coll, Francesc, Keeley, Alexander, Lindsey, Benjamin B, Marek, Aleksandra et al (show 6 more authors)
(2021)
Rapid feedback on hospital onset SARS-CoV-2 infections combining epidemiological and sequencing data.
eLife, 10.
e65828-.
Abstract
<jats:sec id="abs1"><jats:title>Background:</jats:title><jats:p>Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult.</jats:p></jats:sec><jats:sec id="abs2"><jats:title>Methods:</jats:title><jats:p>We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hr following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February–May 2020.</jats:p></jats:sec><jats:sec id="abs3"><jats:title>Results:</jats:title><jats:p>We analysed data from 326 HOCIs. Among HOCIs with time from admission ≥8 days, the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time from admission 3–7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%).</jats:p></jats:sec><jats:sec id="abs4"><jats:title>Conclusions:</jats:title><jats:p>The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period.</jats:p></jats:sec><jats:sec id="abs5"><jats:title>Funding:</jats:title><jats:p>COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.</jats:p></jats:sec>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | COVID-19 Genomics UK (COG-UK) consortium, Humans, Cross Infection, Population Surveillance, Probability, Retrospective Studies, Disease Outbreaks, Genome, Viral, Hospitals, United Kingdom, Whole Genome Sequencing, COVID-19, SARS-CoV-2 |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 12 May 2022 09:51 |
| Last Modified: | 16 Dec 2023 03:36 |
| DOI: | 10.7554/elife.65828 |
| Open Access URL: | https://elifesciences.org/articles/65828 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3154655 |
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