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A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy
First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infec...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6002029/ https://www.ncbi.nlm.nih.gov/pubmed/29928744 http://dx.doi.org/10.1016/j.idm.2017.06.003 |
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author | Zakary, Omar Rachik, Mostafa Elmouki, Ilias |
author_facet | Zakary, Omar Rachik, Mostafa Elmouki, Ilias |
author_sort | Zakary, Omar |
collection | PubMed |
description | First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions. |
format | Online Article Text |
id | pubmed-6002029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-60020292018-06-20 A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy Zakary, Omar Rachik, Mostafa Elmouki, Ilias Infect Dis Model Article First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions. KeAi Publishing 2017-06-30 /pmc/articles/PMC6002029/ /pubmed/29928744 http://dx.doi.org/10.1016/j.idm.2017.06.003 Text en © 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Zakary, Omar Rachik, Mostafa Elmouki, Ilias A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title | A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title_full | A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title_fullStr | A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title_full_unstemmed | A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title_short | A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
title_sort | new epidemic modeling approach: multi-regions discrete-time model with travel-blocking vicinity optimal control strategy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6002029/ https://www.ncbi.nlm.nih.gov/pubmed/29928744 http://dx.doi.org/10.1016/j.idm.2017.06.003 |
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