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Intensity of COVID-19 in care homes following hospital discharge in the early stages of the UK epidemic

Joe Hollinghurst, Laura North, Chris Emmerson, Ashley Akbari Orcid Logo, Fatemeh Torabi Orcid Logo, Chris Williams, Ronan Lyons Orcid Logo, Alan Hawkes, Ed Bennett Orcid Logo, Michael Gravenor Orcid Logo, Rich Fry Orcid Logo

Age and Ageing, Volume: 51, Issue: 5

Swansea University Authors: Joe Hollinghurst, Laura North, Ashley Akbari Orcid Logo, Fatemeh Torabi Orcid Logo, Ronan Lyons Orcid Logo, Alan Hawkes, Ed Bennett Orcid Logo, Michael Gravenor Orcid Logo, Rich Fry Orcid Logo

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DOI (Published version): 10.1093/ageing/afac072

Abstract

BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important trans...

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Published in: Age and Ageing
ISSN: 0002-0729 1468-2834
Published: Oxford University Press (OUP) 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59693
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Abstract: BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events.MethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model.FindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected.InterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.
Keywords: Older people, Hawkes Process, Multi-level model, Linked Data, COVID-19, Hospital discharge, Care homes
College: Swansea University Medical School
Funders: This work was supported by the Medical Research Council [MR/V028367/1]; Health and Care Research Wales [Project: SCF-18-1504]; Health Data Research UK [HDR-9006] which receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK which is funded by the Economic and Social Research Council [grant ES/S007393/1]. E.B. acknowledges the support of the Supercomputing Wales programme, which is part-funded by the European Regional Development Fund (ERDF) via Welsh Government, and of the Science and Technologies Facilities Council Research Software Engineering Fellowship EP/V052489/1.
Issue: 5