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Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda
This paper shows the impact of control measures on the predictive COVID-19 mathematical model in Rwanda through sensitivity analysis of the basic reproduction number [Formula: see text]. We have introduced different levels of the control measures in the model, precisely, 90%, 80%, 60%, 40%, 20%, 0%...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930676/ https://www.ncbi.nlm.nih.gov/pubmed/36819990 http://dx.doi.org/10.1016/j.imu.2023.101195 |
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author | Mpinganzima, Lydie Ntaganda, Jean Marie Banzi, Wellars Muhirwa, Jean Pierre Nannyonga, Betty Kivumbi Niyobuhungiro, Japhet Rutaganda, Eric |
author_facet | Mpinganzima, Lydie Ntaganda, Jean Marie Banzi, Wellars Muhirwa, Jean Pierre Nannyonga, Betty Kivumbi Niyobuhungiro, Japhet Rutaganda, Eric |
author_sort | Mpinganzima, Lydie |
collection | PubMed |
description | This paper shows the impact of control measures on the predictive COVID-19 mathematical model in Rwanda through sensitivity analysis of the basic reproduction number [Formula: see text]. We have introduced different levels of the control measures in the model, precisely, 90%, 80%, 60%, 40%, 20%, 0% and studied their effects on the variation of the model variables. The results from numerical simulations reveal that the more the adherence to the control measures at the percentage of 90%, 80%, 60%, 40%, 20%, 0%, the more the number of COVID-19 cases, hospitalized and deaths reduces which indicates the reduction of the spread of the pandemic in Rwanda. Moreover, It was shown that the transition rate from the infectious compartment is very sensitive to [Formula: see text] as the increase/decrease in its value increases/decreases the value of [Formula: see text] and this leads to the high spread or the containment of the pandemic respectively. |
format | Online Article Text |
id | pubmed-9930676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99306762023-02-16 Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda Mpinganzima, Lydie Ntaganda, Jean Marie Banzi, Wellars Muhirwa, Jean Pierre Nannyonga, Betty Kivumbi Niyobuhungiro, Japhet Rutaganda, Eric Inform Med Unlocked Article This paper shows the impact of control measures on the predictive COVID-19 mathematical model in Rwanda through sensitivity analysis of the basic reproduction number [Formula: see text]. We have introduced different levels of the control measures in the model, precisely, 90%, 80%, 60%, 40%, 20%, 0% and studied their effects on the variation of the model variables. The results from numerical simulations reveal that the more the adherence to the control measures at the percentage of 90%, 80%, 60%, 40%, 20%, 0%, the more the number of COVID-19 cases, hospitalized and deaths reduces which indicates the reduction of the spread of the pandemic in Rwanda. Moreover, It was shown that the transition rate from the infectious compartment is very sensitive to [Formula: see text] as the increase/decrease in its value increases/decreases the value of [Formula: see text] and this leads to the high spread or the containment of the pandemic respectively. The Authors. Published by Elsevier Ltd. 2023 2023-02-13 /pmc/articles/PMC9930676/ /pubmed/36819990 http://dx.doi.org/10.1016/j.imu.2023.101195 Text en © 2023 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 | Article Mpinganzima, Lydie Ntaganda, Jean Marie Banzi, Wellars Muhirwa, Jean Pierre Nannyonga, Betty Kivumbi Niyobuhungiro, Japhet Rutaganda, Eric Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title | Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title_full | Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title_fullStr | Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title_full_unstemmed | Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title_short | Analysis of COVID-19 mathematical model for predicting the impact of control measures in Rwanda |
title_sort | analysis of covid-19 mathematical model for predicting the impact of control measures in rwanda |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930676/ https://www.ncbi.nlm.nih.gov/pubmed/36819990 http://dx.doi.org/10.1016/j.imu.2023.101195 |
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