Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.


Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
07 01 2021
Historique:
entrez: 8 1 2021
pubmed: 9 1 2021
medline: 20 1 2021
Statut: epublish

Résumé

To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case. Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths. SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making. Publicly available data on patients with COVID-19. The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time. SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7). The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.

Identifiants

pubmed: 33414147
pii: bmjopen-2020-041536
doi: 10.1136/bmjopen-2020-041536
pmc: PMC7797241
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e041536

Subventions

Organisme : Medical Research Council
ID : MC_PC_19067
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_19067/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S004769/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V038613/1
Pays : United Kingdom

Informations de copyright

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Ross D Booton (RD)

School of Veterinary Sciences, University of Bristol, Bristol, UK.

Louis MacGregor (L)

Population Health Science Institute, University of Bristol Medical School, Bristol, UK.
NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.

Lucy Vass (L)

School of Veterinary Sciences, University of Bristol, Bristol, UK.
Population Health Science Institute, University of Bristol Medical School, Bristol, UK.

Katharine J Looker (KJ)

Population Health Science Institute, University of Bristol Medical School, Bristol, UK.
NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.

Catherine Hyams (C)

Academic Respiratory Unit, Southmead Hospital, Bristol, UK.

Philip D Bright (PD)

Immunology, Pathology Sciences, North Bristol NHS Trust, Bristol, UK.

Irasha Harding (I)

Consultant in Microbiology, University Hospitals Bristol, Bristol, UK.

Rajeka Lazarus (R)

Consultant in Microbiology and Infectious Diseases, University Hospitals Bristol, Bristol, UK.

Fergus Hamilton (F)

Infection Science, Southmead Hospital, North Bristol NHS Trust, Bristol, UK.

Daniel Lawson (D)

School of Mathematics, University of Bristol, Bristol, UK.

Leon Danon (L)

Population Health Science Institute, University of Bristol Medical School, Bristol, UK.
Department of Engineering Mathematics, University of Bristol, Bristol, UK.
Alan Turing Institute, London, UK.
Health Data Research UK South-West of England Partnership, Bristol, UK.

Adrian Pratt (A)

Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.

Richard Wood (R)

Health Data Research UK South-West of England Partnership, Bristol, UK.
Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.

Ellen Brooks-Pollock (E)

School of Veterinary Sciences, University of Bristol, Bristol, UK.
Population Health Science Institute, University of Bristol Medical School, Bristol, UK.
NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.

Katherine M E Turner (KME)

School of Veterinary Sciences, University of Bristol, Bristol, UK katy.turner@bristol.ac.uk.
Population Health Science Institute, University of Bristol Medical School, Bristol, UK.
NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.
Health Data Research UK South-West of England Partnership, Bristol, UK.

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