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A control theory approach to optimal pandemic mitigation
In the framework of homogeneous susceptible-infected-recovered (SIR) models, we use a control theory approach to identify optimal pandemic mitigation strategies. We derive rather general conditions for reaching herd immunity while minimizing the costs incurred by the introduction of societal control...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7894916/ https://www.ncbi.nlm.nih.gov/pubmed/33606802 http://dx.doi.org/10.1371/journal.pone.0247445 |
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author | Godara, Prakhar Herminghaus, Stephan Heidemann, Knut M. |
author_facet | Godara, Prakhar Herminghaus, Stephan Heidemann, Knut M. |
author_sort | Godara, Prakhar |
collection | PubMed |
description | In the framework of homogeneous susceptible-infected-recovered (SIR) models, we use a control theory approach to identify optimal pandemic mitigation strategies. We derive rather general conditions for reaching herd immunity while minimizing the costs incurred by the introduction of societal control measures (such as closing schools, social distancing, lockdowns, etc.), under the constraint that the infected fraction of the population does never exceed a certain maximum corresponding to public health system capacity. Optimality is derived and verified by variational and numerical methods for a number of model cost functions. The effects of immune response decay after recovery are taken into account and discussed in terms of the feasibility of strategies based on herd immunity. |
format | Online Article Text |
id | pubmed-7894916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-78949162021-03-01 A control theory approach to optimal pandemic mitigation Godara, Prakhar Herminghaus, Stephan Heidemann, Knut M. PLoS One Research Article In the framework of homogeneous susceptible-infected-recovered (SIR) models, we use a control theory approach to identify optimal pandemic mitigation strategies. We derive rather general conditions for reaching herd immunity while minimizing the costs incurred by the introduction of societal control measures (such as closing schools, social distancing, lockdowns, etc.), under the constraint that the infected fraction of the population does never exceed a certain maximum corresponding to public health system capacity. Optimality is derived and verified by variational and numerical methods for a number of model cost functions. The effects of immune response decay after recovery are taken into account and discussed in terms of the feasibility of strategies based on herd immunity. Public Library of Science 2021-02-19 /pmc/articles/PMC7894916/ /pubmed/33606802 http://dx.doi.org/10.1371/journal.pone.0247445 Text en © 2021 Godara et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Godara, Prakhar Herminghaus, Stephan Heidemann, Knut M. A control theory approach to optimal pandemic mitigation |
title | A control theory approach to optimal pandemic mitigation |
title_full | A control theory approach to optimal pandemic mitigation |
title_fullStr | A control theory approach to optimal pandemic mitigation |
title_full_unstemmed | A control theory approach to optimal pandemic mitigation |
title_short | A control theory approach to optimal pandemic mitigation |
title_sort | control theory approach to optimal pandemic mitigation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7894916/ https://www.ncbi.nlm.nih.gov/pubmed/33606802 http://dx.doi.org/10.1371/journal.pone.0247445 |
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