COVID-19: Generate and apply local modelled transmission and morbidity effects to provide an estimate of the variation in overall relative healthcare resource impact at general practice granularity.


Journal

International journal of clinical practice
ISSN: 1742-1241
Titre abrégé: Int J Clin Pract
Pays: India
ID NLM: 9712381

Informations de publication

Date de publication:
Sep 2020
Historique:
received: 23 03 2020
revised: 28 04 2020
accepted: 09 05 2020
pubmed: 12 5 2020
medline: 5 9 2020
entrez: 12 5 2020
Statut: ppublish

Résumé

Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the name given to the 2019 novel coronavirus. COVID-19 is the name given to the disease associated with the virus. SARS-CoV-2 is a new strain of coronavirus not been previously identified in humans. Two key factors, case incidence and case morbidity, were analysed for England. When taken together they give an estimate of relative demand on healthcare utilisation. To analyse case incidence, the latest values for indicators that could be associated with infection transmission rates were collected from the Office of National Statistics (ONS) and Quality Outcome Framework (QOF) sources. These included population density, %age >16, at fulltime work/education, %age over 60, %BME ethnicity, social deprivation as IMD2019, location as latitude/longitude, and patient engagement as %self-confident in their own long-term condition management. Average case morbidity was calculated. To provide a comparative measure of overall healthcare resource impact, individual GP practice impact scores were compared against the median practice. The case incidence regression is a dynamic situation but it currently shows that Urban, %Working, and age >60 were the strongest determinants of case incidence. The local population comorbidity remains unchanged. The range of relative healthcare impact was wide with 80% of practices falling at 20%-250% of the national median. Once practice population numbers were included we found that the top 33% of GP practices supporting 45% of the patient population would require 68% of COVID-19 healthcare resources. The model provides useful information about the relative impact of Covid-19 on healthcare workload at GP practice granularity in all parts of England. Covid-19 is impacting on the utilisation of health/social care resources across the world. This model provides a way of predicting relative local levels of disease burden based on defined criteria, thereby providing a method for targeting limited care resources to optimise national/regional/local responses to the COVID-19 outbreak.

Identifiants

pubmed: 32392377
doi: 10.1111/ijcp.13533
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e13533

Informations de copyright

© 2020 The Authors. International Journal of Clinical Practice published by John Wiley & Sons Ltd.

Références

European Centre for Disease Prevention and Control; 2020. https://www.ecdc.europa.eu/en/novel-coronavirus-china/questions-answers. Accessed 16 March 2020.
WHO COVID-19 Situation Report 54. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200314-sitrep-54-covid-19.pdf?sfvrsn=dcd46351_6. Accessed 16 March 2020.
Kings Fund; 2020. https://www.kingsfund.org.uk/blog/2020/03/spring-budget-mean-health-and-care. Accessed 16 March 2020.
Stein, M.L., Rudge, J.W., Coker, R., et al. 2012. Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator. BMC public health, 12(1), 870. https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-12-870. Accessed 16 March 2020.
https://www.gov.uk/guidance/coronavirus-covid-19-information-for-the-public. Accessed 16 March 2020.
Estimation of risk factors for COVID-19 mortality - preliminary results Francisco Caramelo, Nuno Ferreira, Barbara Oliveiros. https://doi.org/10.1101/2020.02.24.20027268

Auteurs

Mike Stedman (M)

Res Consortium, Andover, Hampshire, UK.

Mark Lunt (M)

The Faculty of Biology, Medicine and Health and Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.

Mark Davies (M)

Res Consortium, Andover, Hampshire, UK.

Martin Gibson (M)

Department of Diabetes and Endocrinology, Salford, UK.

Adrian Heald (A)

The Faculty of Biology, Medicine and Health and Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Department of Diabetes and Endocrinology, Salford, UK.

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