Testing, tracing and isolation in compartmental models
Testing, tracing and isolation in compartmental models
Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computational efficiency is such that it can be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.
Sturniolo, Simone
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Waites, William
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Colbourn, Tim
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Manheim, David
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Panovska-Griffiths, Jasmina
da117053-d638-4ccc-b527-d2e06e5bbb7a
Regoes, Roland R.
59144133-afa4-4533-8ca7-a2591c83b598
4 March 2021
Sturniolo, Simone
07c980cc-9ac5-451a-b26c-4ddbd5ef72b9
Regoes, Roland R.
59144133-afa4-4533-8ca7-a2591c83b598
Waites, William
a069e5ff-f440-4b89-ae81-3b58c2ae2afd
Colbourn, Tim
535eccc8-5ccc-4d66-b133-cb6eadb6776f
Manheim, David
1b68c6bd-1dc0-4a70-bb0c-e681f836bf02
Panovska-Griffiths, Jasmina
da117053-d638-4ccc-b527-d2e06e5bbb7a
Sturniolo, Simone, Waites, William, Colbourn, Tim, Manheim, David and Panovska-Griffiths, Jasmina
,
Regoes, Roland R.
(ed.)
(2021)
Testing, tracing and isolation in compartmental models.
PLoS Computational Biology, 17 (3).
(doi:10.1371/journal.pcbi.1008633).
Abstract
Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computational efficiency is such that it can be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.
Text
journal.pcbi.1008633
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Accepted/In Press date: 14 December 2020
Published date: 4 March 2021
Identifiers
Local EPrints ID: 500103
URI: http://eprints.soton.ac.uk/id/eprint/500103
ISSN: 1553-734X
PURE UUID: 2bed0624-696a-4a0c-bd3d-0695a9eb3daa
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Date deposited: 15 Apr 2025 16:58
Last modified: 22 Aug 2025 02:43
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Contributors
Author:
Simone Sturniolo
Editor:
Roland R. Regoes
Author:
William Waites
Author:
Tim Colbourn
Author:
David Manheim
Author:
Jasmina Panovska-Griffiths
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