1. Characterising within-hospitalSARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves.
- Author
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Lindsey BB, Villabona-Arenas CJ, Campbell F, Keeley AJ, Parker MD, Shah DR, Parsons H, Zhang P, Kakkar N, Gallis M, Foulkes BH, Wolverson P, Louka SF, Christou S, State A, Johnson K, Raza M, Hsu S, Jombart T, Cori A, Evans CM, Partridge DG, Atkins KE, Hué S, and de Silva TI
- Subjects
- Bayes Theorem, Cohort Studies, Cross Infection epidemiology, Cross Infection transmission, Disease Outbreaks, Genomics, Health Personnel, Hospitals, Humans, United Kingdom epidemiology, COVID-19 epidemiology, COVID-19 transmission, Genome, Viral, Molecular Epidemiology, Pandemics, SARS-CoV-2 genetics
- Abstract
Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th J'uly 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains., (© 2022. The Author(s).)
- Published
- 2022
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