Modelling presymptomatic infectiousness in COVID-19
Modelling presymptomatic infectiousness in COVID-19
This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment model. Both models can be fitted to real data as they include parameters that can be estimated from the data. SEPIR deploys an additional presymptomatic infectious compartment, not modelled in SEIR but known to exist in COVID-19. This stage can also be fitted to data. We focus on how to fit SEPIR to a first wave of COVID. Both SEIR and SEPIR and the existing SEIR models assume a homogeneous mixing population with parameters fixed. Moreover, neither includes dynamically varying control strategies deployed against the virus. If either model is to represent more than just a single wave of the epidemic, then the parameters of the model would have to be time dependent. In view of this, we also show how reproduction numbers can be calculated to investigate the long-term overall outcome of an epidemic.
differential equation epidemic models, asymptomatic transmission, effective reproduction number, parametric models
532-543
Cheng, Russell
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Dye, Christopher
73ab1d1e-80ee-496e-9765-6842739fd843
Dagpunar, John
be796c6f-4b91-462b-b7ef-c9387efc26dc
Williams, Brian
b92e9a04-6b8a-4a8e-9661-9d89898f9273
3 September 2023
Cheng, Russell
a4296b4e-7693-4e5f-b3d5-27b617bb9d67
Dye, Christopher
73ab1d1e-80ee-496e-9765-6842739fd843
Dagpunar, John
be796c6f-4b91-462b-b7ef-c9387efc26dc
Williams, Brian
b92e9a04-6b8a-4a8e-9661-9d89898f9273
Cheng, Russell, Dye, Christopher, Dagpunar, John and Williams, Brian
(2023)
Modelling presymptomatic infectiousness in COVID-19.
Journal of Simulation, 17 (5), .
(doi:10.1080/17477778.2023.2190467).
Abstract
This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment model. Both models can be fitted to real data as they include parameters that can be estimated from the data. SEPIR deploys an additional presymptomatic infectious compartment, not modelled in SEIR but known to exist in COVID-19. This stage can also be fitted to data. We focus on how to fit SEPIR to a first wave of COVID. Both SEIR and SEPIR and the existing SEIR models assume a homogeneous mixing population with parameters fixed. Moreover, neither includes dynamically varying control strategies deployed against the virus. If either model is to represent more than just a single wave of the epidemic, then the parameters of the model would have to be time dependent. In view of this, we also show how reproduction numbers can be calculated to investigate the long-term overall outcome of an epidemic.
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Modelling presymptomatic infectiousness in COVID 19
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Accepted/In Press date: 7 March 2023
e-pub ahead of print date: 23 March 2023
Published date: 3 September 2023
Keywords:
differential equation epidemic models, asymptomatic transmission, effective reproduction number, parametric models
Identifiers
Local EPrints ID: 477210
URI: http://eprints.soton.ac.uk/id/eprint/477210
ISSN: 1747-7778
PURE UUID: 58615e83-a783-416b-b25b-735521bc3ec7
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Date deposited: 01 Jun 2023 16:40
Last modified: 22 Mar 2024 05:01
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Author:
Christopher Dye
Author:
Brian Williams
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