Evidence map›Paper›PMID 36564506›Full record

ArticleCommunications medicine2022

Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic.

Jared K Wilson-Aggarwal, Nick Gotts, Wai Keong Wong, Chris Liddington, Simon Knight, Moira J Spyer, Catherine F Houlihan, Eleni Nastouli, Ed Manley

Abstract read
In one paragraph

Article in Communications medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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. Article
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

9 authors.

Jared K Wilson-AggarwalSchool of Geography, University of Leeds, Woodhouse, Leeds, LS2 9JT, UK.ORCID http://orcid.org/0000-0001-9156-8897
Nick GottsSchool of Geography, University of Leeds, Woodhouse, Leeds, LS2 9JT, UK.
Wai Keong WongDepartment of Digital Healthcare Technology, University College London Hospitals NHS Foundation Trust, London, UK.ORCID http://orcid.org/0000-0002-5742-0108
Chris LiddingtonDepartment of Digital Healthcare Technology, University College London Hospitals NHS Foundation Trust, London, UK.
Simon KnightDepartment of Digital Healthcare Technology, University College London Hospitals NHS Foundation Trust, London, UK.
Moira J SpyerDepartment of Infection, Immunity and Inflammation, UCL GOS Institute of Child Health University College London, London, UK.
Catherine F HoulihanDepartment of Infection, Immunity and Inflammation, UCL GOS Institute of Child Health University College London, London, UK.
Eleni NastouliDepartment of Infection, Immunity and Inflammation, UCL GOS Institute of Child Health University College London, London, UK.ORCID http://orcid.org/0000-0002-1684-2013
Ed ManleySchool of Geography, University of Leeds, Woodhouse, Leeds, LS2 9JT, UK. E.J.Manley@leeds.ac.uk.ORCID http://orcid.org/0000-0002-8904-0513

Funding

RCUK | Medical Research Council (MRC) MC_PC_19082
6 · The paper itself

Abstract

backgroundInsights into behaviours relevant to the transmission of infections are extremely valuable for epidemiological investigations. Healthcare worker (HCW) mobility and patient contacts within the hospital can contribute to nosocomial outbreaks, yet data on these behaviours are often limited.

methodsUsing electronic medical records and door access logs from a London teaching hospital during the COVID-19 pandemic, we derive indicators for HCW mobility and patient contacts at an aggregate level. We assess the spatial-temporal variations in HCW behaviour and, to demonstrate the utility of these behavioural markers, investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs).

resultsFluctuations in HCW mobility and patient contacts were identified during the pandemic, with the most prominent changes in behaviour on floors handling the majority of COVID-19 patients. The connectivity between floors was disrupted by the pandemic and, while this stabilised after the first wave, the interconnectivity of COVID-19 and non-COVID-19 wards always featured. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting in response to the number of COVID-19 patients in the hospital.

conclusionsRoutinely collected electronic records in the healthcare environment provide a means to rapidly assess and investigate behaviour change in the HCW population, and can support evidence based infection prevention and control activities. Integrating frameworks like ours into routine practice will empower decision makers and improve pandemic preparedness by providing tools to help curtail nosocomial outbreaks of communicable diseases.

Identifiers

PMID36564506
PMCPMC9782286

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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.