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Establishing an SEIR-based framework for local modelling of COVID-19 infections, hospitalisations and deaths.
Wood, R M; Pratt, A C; Murch, B J; Powell, A L; Booton, R D; Thomas, D G; Twigger, J; Diakou, E; Coleborn, S; Manning, T; Davies, C; Turner, K M.
  • Wood RM; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
  • Pratt AC; School of Management, University of Bath, Bath, UK.
  • Murch BJ; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
  • Powell AL; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
  • Booton RD; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
  • Thomas DG; Bristol Medical School, University of Bristol, Bristol, UK.
  • Twigger J; Public Health, Bristol City Council, Bristol, UK.
  • Diakou E; Public Health, Bristol City Council, Bristol, UK.
  • Coleborn S; Business Intelligence, North Somerset Council, Weston-Super-Mare, UK.
  • Manning T; Public Health, South Gloucestershire Council, Yate, UK.
  • Davies C; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
  • Turner KM; Bristol, North Somerset and South Gloucestershire CCG, National Health Service, Bristol, UK.
Health Syst (Basingstoke) ; 10(4): 337-347, 2021.
Article in English | MEDLINE | ID: covidwho-1390343
ABSTRACT
Without timely assessments of the number of COVID-19 cases requiring hospitalisation, healthcare providers will struggle to ensure an appropriate number of beds are made available. Too few could cause excess deaths while too many could result in additional waits for elective treatment. As well as supporting capacity considerations, reliably projecting future "waves" is important to inform the nature, timing and magnitude of any localised restrictions to reduce transmission. In making the case for locally owned and locally configurable models, this paper details the approach taken by one major healthcare system in founding a multi-disciplinary "Scenario Review Working Group", comprising commissioners, public health officials and academic epidemiologists. The role of this group, which met weekly during the pandemic, was to define and maintain an evolving library of plausible scenarios to underpin projections obtained through an SEIR-based compartmental model. Outputs have informed decision-making at the system's major incident Bronze, Silver and Gold Commands. This paper presents illustrated examples of use and offers practical considerations for other healthcare systems that may benefit from such a framework.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Health Syst (Basingstoke) Year: 2021 Document Type: Article Affiliation country: 20476965.2021.1973348

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Health Syst (Basingstoke) Year: 2021 Document Type: Article Affiliation country: 20476965.2021.1973348