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Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model

Consider a Markovian SIR epidemic model in a homogeneous community. To this model we add a rate at which individuals are tested, and once an infectious individual tests positive it is isolated and each of their contacts are traced and tested independently with some fixed probability. If such a trace...

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Autores principales: Zhang, Dongni, Britton, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400008/
https://www.ncbi.nlm.nih.gov/pubmed/36001175
http://dx.doi.org/10.1007/s11538-022-01065-9
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author Zhang, Dongni
Britton, Tom
author_facet Zhang, Dongni
Britton, Tom
author_sort Zhang, Dongni
collection PubMed
description Consider a Markovian SIR epidemic model in a homogeneous community. To this model we add a rate at which individuals are tested, and once an infectious individual tests positive it is isolated and each of their contacts are traced and tested independently with some fixed probability. If such a traced individual tests positive it is isolated, and the contact tracing is iterated. This model is analysed using large population approximations, both for the early stage of the epidemic when the “to-be-traced components” of the epidemic behaves like a branching process, and for the main stage of the epidemic where the process of to-be-traced components converges to a deterministic process defined by a system of differential equations. These approximations are used to quantify the effect of testing and of contact tracing on the effective reproduction numbers (for the components as well as for the individuals), the probability of a major outbreak, and the final fraction getting infected. Using numerical illustrations when rates of infection and natural recovery are fixed, it is shown that Test-and-Trace strategy is effective in reducing the reproduction number. Surprisingly, the reproduction number for the branching process of components is not monotonically decreasing in the tracing probability, but the individual reproduction number is conjectured to be monotonic as expected. Further, in the situation where individuals also self-report for testing, the tracing probability is more influential than the screening rate (measured by the fraction infected being screened).
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spelling pubmed-94000082022-08-24 Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model Zhang, Dongni Britton, Tom Bull Math Biol Original Article Consider a Markovian SIR epidemic model in a homogeneous community. To this model we add a rate at which individuals are tested, and once an infectious individual tests positive it is isolated and each of their contacts are traced and tested independently with some fixed probability. If such a traced individual tests positive it is isolated, and the contact tracing is iterated. This model is analysed using large population approximations, both for the early stage of the epidemic when the “to-be-traced components” of the epidemic behaves like a branching process, and for the main stage of the epidemic where the process of to-be-traced components converges to a deterministic process defined by a system of differential equations. These approximations are used to quantify the effect of testing and of contact tracing on the effective reproduction numbers (for the components as well as for the individuals), the probability of a major outbreak, and the final fraction getting infected. Using numerical illustrations when rates of infection and natural recovery are fixed, it is shown that Test-and-Trace strategy is effective in reducing the reproduction number. Surprisingly, the reproduction number for the branching process of components is not monotonically decreasing in the tracing probability, but the individual reproduction number is conjectured to be monotonic as expected. Further, in the situation where individuals also self-report for testing, the tracing probability is more influential than the screening rate (measured by the fraction infected being screened). Springer US 2022-08-24 2022 /pmc/articles/PMC9400008/ /pubmed/36001175 http://dx.doi.org/10.1007/s11538-022-01065-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Zhang, Dongni
Britton, Tom
Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title_full Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title_fullStr Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title_full_unstemmed Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title_short Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model
title_sort analysing the effect of test-and-trace strategy in an sir epidemic model
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9400008/
https://www.ncbi.nlm.nih.gov/pubmed/36001175
http://dx.doi.org/10.1007/s11538-022-01065-9
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