Evidence map›Paper›PMID 37083855›Full record

ArticlePloS one2023

Assessing spatiotemporal variability in SARS-CoV-2 infection risk for hospital workers using routinely-collected data.

Jared K Wilson-Aggarwal, Nick Gotts, Kellyn Arnold, Moira J Spyer, Catherine F Houlihan, Eleni Nastouli, Ed Manley

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 54% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Jared K Wilson-AggarwalSchool of Geography, University of Leeds, Woodhouse, Leeds, United Kingdom.ORCID 0000-0001-9156-8897
Nick GottsSchool of Geography, University of Leeds, Woodhouse, Leeds, United Kingdom.
Kellyn ArnoldSchool of Geography, University of Leeds, Woodhouse, Leeds, United Kingdom.
Moira J SpyerDepartment of Clinical Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom.
Catherine F HoulihanDepartment of Clinical Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom.
Eleni NastouliDepartment of Clinical Virology, University College London Hospitals NHS Foundation Trust, London, United Kingdom.
Ed ManleySchool of Geography, University of Leeds, Woodhouse, Leeds, United Kingdom.ORCID 0000-0002-8904-0513
University of Leeds · GBUniversity College London Hospitals NHS Foundation Trust · GB

Funding

Department of HealthMedical Research Council MC_PC_19082
6 · The paper itself

Abstract

The COVID-19 pandemic has emphasised the need to rapidly assess infection risks for healthcare workers within the hospital environment. Using data from the first year of the pandemic, we investigated whether an individual's COVID-19 test result was associated with behavioural markers derived from routinely collected hospital data two weeks prior to a test. The temporal and spatial context of behaviours were important, with the highest risks of infection during the first wave, for staff in contact with a greater number of patients and those with greater levels of activity on floors handling the majority of COVID-19 patients. Infection risks were higher for BAME staff and individuals working more shifts. Night shifts presented higher risks of infection between waves of COVID-19 patients. Our results demonstrate the epidemiological relevance of deriving markers of staff behaviour from electronic records, which extend beyond COVID-19 with applications for other communicable diseases and in supporting pandemic preparedness.

Indexed as

COVID-19Health PersonnelHospitalsHumansPandemicsPersonnel, HospitalRoutinely Collected Health DataSARS-CoV-2

Identifiers

PMID37083855
PMCPMC10121006
OpenAlexW4366603741

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.