ArticleThe Journal of infection2021
Genetic epidemiology of SARS-CoV-2 transmission in renal dialysis units - A high risk community-hospital interface.
Article in The Journal of infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Status of COVID-19 vaccination in patients undergoing dialysis in China: a national cross-sectional study (2022).Frontiers in public health · 2025Article
- Impact of arteriovenous fistula formation on trajectory of kidney function decline: a target trial emulation.Clinical kidney journal · 2024Article
- Article
- SARS-CoV2 antibody response after a third dose of heterologous ChAdOx1 nCoV-19 and Moderna vaccine in chronic dialysis patients.The Journal of infection · 2022Article
- Omicron neutralising antibodies after COVID-19 vaccination in haemodialysis patients.Lancet (London, England) · 2022Article
- Pango lineage designation and assignment using SARS-CoV-2 spike gene nucleotide sequences.BMC genomics · 2022Article
- Genomics-informed outbreak investigations of SARS-CoV-2 using civet.PLOS global public health · 2022Article
- Neutralising antibodies after COVID-19 vaccination in UK haemodialysis patients.Lancet (London, England) · 2021Article
Corrections and comments
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Authors and funding
43 authors.
Funding
Abstract
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.
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Registered trials
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