Author: Lindsey, B. B.; Villabona-Arenas, C. J.; Campbell, F.; Keeley, A. J.; Parker, M. D.; Shah, D. R.; Parsons, H.; Zhang, P.; Kakkar, N.; Gallis, M.; Foulkes, B. H.; Wolverson, P.; Louka, S. F.; Christou, S.; State, A.; Johnson, K.; Raza, M.; Hsu, S.; Jombart, T.; Cori, A.; Sheffield COVID-19 Genomics Group,; The COVID-19 Genomics UK consortium,; CMMID COVID-19 working group,; Evans, C. M.; Partridge, D. G.; Atkins, K. E.; Hue, S.; de Silva, T. I.
Title: Characterising within-hospital SARS-CoV-2 transmission events: a retrospective analysis integrating epidemiological and viral genomic data from a UK tertiary care setting across two pandemic waves Cord-id: m4fcw7lk Document date: 2021_7_19
ID: m4fcw7lk
Snippet: Objectives - To characterise within-hospital SARS-CoV-2 transmission across two waves of the COVID-19 pandemic. Design - A retrospective Bayesian modelling study to reconstruct transmission chains amongst 2181 patients and healthcare workers using combined viral genomic and epidemiological data. Setting - A large UK NHS Trust with over 1400 beds and employing approximately 17,000 staff. Participants - 780 patients and 522 staff testing SARS-CoV-2 positive between 1st March 2020 and 25th July 202
Document: Objectives - To characterise within-hospital SARS-CoV-2 transmission across two waves of the COVID-19 pandemic. Design - A retrospective Bayesian modelling study to reconstruct transmission chains amongst 2181 patients and healthcare workers using combined viral genomic and epidemiological data. Setting - A large UK NHS Trust with over 1400 beds and employing approximately 17,000 staff. Participants - 780 patients and 522 staff testing SARS-CoV-2 positive between 1st March 2020 and 25th July 2020 (Wave 1); and 580 patients and 299 staff testing SARS-CoV-2 positive between 30th November 2020 and 24th January 2021 (Wave 2). Main outcome measures - Transmission pairs including who-infected-whom; location of transmission events in hospital; number of secondary cases from each individual, including differences in onward transmission from community and hospital onset patient cases. Results - Staff-to-staff transmission was estimated to be the most frequent transmission type during Wave 1 (31.6% of observed hospital-acquired infections; 95% CI 26.9 to 35.8%), decreasing to 12.9% (95% CI 9.5 to 15.9%) in Wave 2. Patient-to-patient transmissions increased from 27.1% in Wave 1 (95% CI 23.3 to 31.4%) to 52.1% (95% CI 48.0 to 57.1%) in Wave 2, to become the predominant transmission type. Over 50% of hospital-acquired infections were concentrated in 8/120 locations in Wave 1 and 10/93 locations in Wave 2. Approximately 40% to 50% of hospital-onset patient cases resulted in onward transmission compared to less than 4% of definite community-acquired cases. Conclusions - Prevention and control measures that evolved during the COVID-19 pandemic may have had a significant impact on reducing infections between healthcare workers, but were insufficient during the second wave to prevent a high number of patient-to-patient transmissions. As hospital-acquired cases appeared to drive most onward transmissions, more frequent and rapid identification and isolation of these cases will be required to break hospital transmission chains in subsequent pandemic waves
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