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Optimal control of the SIR model in the presence of transmission and treatment uncertainty
The COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes, or submodels, of the...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833871/ https://www.ncbi.nlm.nih.gov/pubmed/33460674 http://dx.doi.org/10.1016/j.mbs.2021.108539 |
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author | Gatto, Nicole M. Schellhorn, Henry |
author_facet | Gatto, Nicole M. Schellhorn, Henry |
author_sort | Gatto, Nicole M. |
collection | PubMed |
description | The COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes, or submodels, of the stochastic SIR model, where the population consists of three groups: susceptible, infected and recovered and dead. In the first regime the proportion of infected is very low, and the proportion of susceptible is very close to 100the proportion of infected is moderate, but not negligible. We show that the first regime corresponds almost exactly to a well-known problem in finance, the problem of portfolio and consumption decisions under mean-reverting returns (Wachter, JFQA 2002), for which the optimal control has an analytical solution. We develop a perturbative solution for the second problem. To our knowledge, this paper represents one of the first attempts to develop analytical/perturbative solutions, as opposed to numerical solutions to stochastic SIR models. |
format | Online Article Text |
id | pubmed-7833871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78338712021-01-26 Optimal control of the SIR model in the presence of transmission and treatment uncertainty Gatto, Nicole M. Schellhorn, Henry Math Biosci Original Research Article The COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes, or submodels, of the stochastic SIR model, where the population consists of three groups: susceptible, infected and recovered and dead. In the first regime the proportion of infected is very low, and the proportion of susceptible is very close to 100the proportion of infected is moderate, but not negligible. We show that the first regime corresponds almost exactly to a well-known problem in finance, the problem of portfolio and consumption decisions under mean-reverting returns (Wachter, JFQA 2002), for which the optimal control has an analytical solution. We develop a perturbative solution for the second problem. To our knowledge, this paper represents one of the first attempts to develop analytical/perturbative solutions, as opposed to numerical solutions to stochastic SIR models. The Authors. Published by Elsevier Inc. 2021-03 2021-01-15 /pmc/articles/PMC7833871/ /pubmed/33460674 http://dx.doi.org/10.1016/j.mbs.2021.108539 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Research Article Gatto, Nicole M. Schellhorn, Henry Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title | Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title_full | Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title_fullStr | Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title_full_unstemmed | Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title_short | Optimal control of the SIR model in the presence of transmission and treatment uncertainty |
title_sort | optimal control of the sir model in the presence of transmission and treatment uncertainty |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833871/ https://www.ncbi.nlm.nih.gov/pubmed/33460674 http://dx.doi.org/10.1016/j.mbs.2021.108539 |
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