Genetic epidemiology of SARS-CoV-2 transmission in renal dialysis units - a high risk community-hospital interface
| Autor: | Joseph Hughes, Oliver Stirrup, Alison Taylor, Natasha Johnson, Kathy Li, Rory Gunson, James Shepherd, Josh Singer, Jennifer S Lees, Yasmin A Parr, Judith G Breuer, Aislynn Taggart, Timothy Willem Jones, Y. Mun Woo, David Robertson, Patrick B. Mark, Igor Starinskij, Vattipally B. Sreenu, Marc Niebel, E. Thomson, Elihu Aranday-Cortes, Scott T W Morris, Ana da Silva Filipe, Natasha Jesudason, Daniel Mair, Jamie P. Traynor, Rajiv Shah, Kyriaki Nomikou, Antonia Ho, Zoe Cousland, Kirstyn Brunker, Alasdair MacLean, Colin C. Geddes, Peter C. Thomson, Sarah E. McDonald, Stephen Carmichael, Jonathan Price, Jenna Nichols, Carlos Varon Lopez, Patawee Asamaphan, Lily Tong, Katherine Smollett |
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| Přispěvatelé: | Mair, Daniel [0000-0001-7169-9080], Nomikou, Kyriaki [0000-0002-7013-1853], Niebel, Marc [0000-0003-2515-6151], Shah, Rajiv [0000-0002-2827-5108], Jones, Timothy PW [0000-0001-6147-6748], Starinskij, Igor [0000-0001-8585-5929], Mark, Patrick B [0000-0003-3387-2123], Apollo - University of Cambridge Repository |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Infection control Renal Dialysis Epidemiology medicine Humans Molecular Epidemiology SARS-CoV-2 business.industry Transmission (medicine) fungi COVID-19 Outbreak Bayes Theorem Renal dialysis unit Hospitals Community hospital Rapid sequencing Haemodialysis Increased risk Genetic epidemiology Emergency medicine Dialysis unit Nosocomial business |
| Popis: | ObjectivesPatients requiring haemodialysis are at increased risk of serious illness with SARS-CoV-2 infection. To improve the understanding of transmission risks in six Scottish renal dialysis units, we utilised the rapid whole-genome sequencing data generated by the COG-UK consortium.MethodsWe combined geographical, temporal and genomic sequence data from the community and hospital to estimate the probability of infection originating from within the dialysis unit, the hospital or the community using Bayesian statistical modelling and compared these results to the details of epidemiological investigations.ResultsOf 671 patients, 60 (8.9%) became infected with SARS-CoV-2, of whom 16 (27%) died. Within-unit and community transmission were both evident and an instance of transmission from the wider hospital setting was also demonstrated.ConclusionsNear-real-time SARS-CoV-2 sequencing data can facilitate tailored infection prevention and control measures, which can be targeted at reducing risk in these settings. |
| Databáze: | OpenAIRE |
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