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Elife . Reconstruction of transmission chains of SARS-CoV-2 amidst multiple outbreaks in a geriatric acute-care hospital: a combined retrospective e

tetano

Editor, Senior Moderator
Elife


. 2022 Jul 19;11:e76854.
doi: 10.7554/eLife.76854. Online ahead of print.
Reconstruction of transmission chains of SARS-CoV-2 amidst multiple outbreaks in a geriatric acute-care hospital: a combined retrospective epidemiological and genomic study


Mohamed Abbas[SUP] 1 [/SUP], Dr Anne Cori[SUP] 2 [/SUP], Samuel Cordey[SUP] 3 [/SUP], Florian Laubscher[SUP] 1 [/SUP], Tomás Robalo Nunes[SUP] 1 [/SUP], Ashleigh Myall[SUP] 4 [/SUP], Julien Salamun[SUP] 5 [/SUP], Philippe Huber[SUP] 6 [/SUP], Dina Zekry[SUP] 6 [/SUP], Virginie Prendki[SUP] 6 [/SUP], Anne Iten[SUP] 1 [/SUP], Laure Vieux[SUP] 7 [/SUP], Valérie Sauvan[SUP] 1 [/SUP], Christophe E Graf[SUP] 7 [/SUP], Stephan Harbarth[SUP] 1 [/SUP]



Affiliations

Abstract

Background: There is ongoing uncertainty regarding transmission chains and the respective roles of healthcare workers (HCWs) and elderly patients in nosocomial outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in geriatric settings.
Methods: We performed a retrospective cohort study including patients with nosocomial coronavirus disease 2019 (COVID-19) in four outbreak-affected wards, and all SARS-CoV-2 RT-PCR positive HCWs from a Swiss university-affiliated geriatric acute-care hospital that admitted both Covid-19 and non-Covid-19 patients during the first pandemic wave in Spring 2020. We combined epidemiological and genetic sequencing data using a Bayesian modelling framework, and reconstructed transmission dynamics of SARS-CoV-2 involving patients and HCWs, to determine who infected whom. We evaluated general transmission patterns according to case type (HCWs working in dedicated Covid-19 cohorting wards: HCW[SUB]covid[/SUB]; HCWs working in non-Covid-19 wards where outbreaks occurred: HCW[SUB]outbreak[/SUB]; patients with nosocomial Covid-19: patient[SUB]noso[/SUB]) by deriving the proportion of infections attributed to each case type across all posterior trees and comparing them to random expectations.
Results: During the study period (March 1 to May 7, 2020) we included 180 SARS-CoV-2 positive cases: 127 HCWs (91 HCW[SUB]covid[/SUB], 36 HCW[SUB]outbreak[/SUB]) and 53 patients. The attack rates ranged from 10-19% for patients, and 21% for HCWs. We estimated that 16 importation events occurred with high confidence (four patients, 12 HCWs) that jointly led to up to 41 secondary cases; in six additional cases (five HCWs, one patient), importation was possible with a posterior between 10-50%. Most patient-to-patient transmission events involved patients having shared a ward (95.2%, 95% credible interval [CrI] 84.2-100%), in contrast to those having shared a room (19.7%, 95%CrI 6.7-33.3%). Transmission events tended to cluster by case type: patient[SUB]noso[/SUB] were almost twice as likely to be infected by other patient[SUB]noso[/SUB] than expected (observed:expected ratio 2.16, 95%CrI 1.17 - 4.20, p = 0.006); similarly, HCW[SUB]outbreak[/SUB] were more than twice as likely to be infected by other HCW[SUB]outbreak[/SUB] than expected (2.72, 95%CrI 0.87-9.00, p = 0.06). The proportion of infectors being HCW[SUB]covid[/SUB] was as expected as random. We found a trend toward a greater proportion of high transmitters (≥2 secondary cases) among HCW[SUB]outbreak[/SUB] than patient[SUB]noso[/SUB] in the late phases (28.6% vs. 11.8%) of the outbreak, although this was not statistically significant.
Conclusions: Most importation events were linked to HCW. Unexpectedly, transmission between HCW[SUB]covid[/SUB] was more limited than transmission between patients and HCW[SUB]outbreak[/SUB]. This finding highlights gaps in infection control and suggests possible areas of improvements to limit the extent of nosocomial transmission.
Funding: This work was supported by a grant from the Swiss National Science Foundation under the NRP78 funding scheme (Grant no. 4078P0_198363).
 
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