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Differential occupational risks to healthcare workers from SARS-CoV-2: a prospective observational study

Abstract:
Background
Personal protective equipment (PPE) and social distancing are designed to mitigate risk of occupational SARS-CoV-2 infection in hospitals. Why healthcare workers nevertheless remain at increased risk is uncertain.
Methods
We conducted voluntary Covid-19 testing programmes for symptomatic and asymptomatic staff at a UK teaching hospital using nasopharyngeal PCR testing and immunoassays for IgG antibodies. A positive result by either modality determined a composite outcome. Risk-factors for Covid-19 were investigated using multivariable logistic regression.
Results
1083/9809(11.0%) staff had evidence of Covid-19 at some time and provided data on potential risk-factors. Staff with a confirmed household contact were at greatest risk (adjusted odds ratio [aOR] 4.63 [95%CI 3.30-6.50]). Higher rates of Covid-19 were seen in staff working in Covid-19-facing areas (21.2% vs. 8.2% elsewhere) (aOR 2.49 [2.00-3.12]). Controlling for Covid-19-facing status, risks were heterogenous across the hospital, with higher rates in acute medicine (1.50 [1.05-2.15]) and sporadic outbreaks in areas with few or no Covid-19 patients. Covid-19 intensive care unit (ICU) staff were relatively protected (0.46 [0.29-0.72]). Positive results were more likely in Black (1.61 [1.20-2.16]) and Asian (1.58 [1.34-1.86]) staff, independent of role or working location, and in porters and cleaners (1.93 [1.25-2.97]). Contact tracing around asymptomatic staff did not lead to enhanced case identification. 24% of staff/patients remained PCR-positive at ≥6 weeks post-diagnosis.
Conclusions
Increased Covid-19 risk was seen in acute medicine, among Black and Asian staff, and porters and cleaners. A bundle of PPE-related interventions protected staff in ICU.
Publication status:
Published
Peer review status:
Not peer reviewed

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Preprint server copy:
10.1101/2020.06.24.20135038

Authors

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Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Sub department:
Big Data Institute - NDPH
Role:
Author
ORCID:
0000-0001-5095-6367
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author


More from this funder
Funder identifier:
https://ror.org/05q2q3076
Grant:
MRF-145-004-TPG-AVISO
Programme:
National PhD Training Programme
More from this funder
Funder identifier:
https://ror.org/029chgv08
Grant:
216417/Z/19/Z
095541/A/11/Z
110110/Z/15/Z
214560/Z/18/Z
More from this funder
Funder identifier:
https://ror.org/03x94j517
Grant:
MR/N00065X/1
MR/V001329/1
More from this funder
Funder identifier:
https://ror.org/019af4n30
Grant:
115766
More from this funder
Funder identifier:
https://ror.org/0187kwz08
Grant:
CL-2018-13-007
HPRU-2012-10041


Preprint server:
medRxiv
Publication date:
2020-06-29
DOI:


Language:
English
Pubs id:
1161803
Local pid:
pubs:1161803
Source identifiers:
W3037782619
Deposit date:
2026-03-27
ARK identifier:

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