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Mathematical modelling of COVID-19: A case study of Italy
This manuscript describes a mathematical epidemiological model of COVID-19 to investigate the dynamics of this pandemic disease and we have fitted this model to the current COVID-19 cases in Italy. We have obtained the basic reproduction number which plays a crucial role on the stability of disease...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8603917/ https://www.ncbi.nlm.nih.gov/pubmed/34840409 http://dx.doi.org/10.1016/j.matcom.2021.11.008 |
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author | Ghosh, Jayanta Kumar Biswas, Sudhanshu Kumar Sarkar, Susmita Ghosh, Uttam |
author_facet | Ghosh, Jayanta Kumar Biswas, Sudhanshu Kumar Sarkar, Susmita Ghosh, Uttam |
author_sort | Ghosh, Jayanta Kumar |
collection | PubMed |
description | This manuscript describes a mathematical epidemiological model of COVID-19 to investigate the dynamics of this pandemic disease and we have fitted this model to the current COVID-19 cases in Italy. We have obtained the basic reproduction number which plays a crucial role on the stability of disease free equilibrium point. Backward bifurcation with respect to the cure rate of treatment occurs conditionally. It is clear from the sensitivity analysis that the developments of self immunities with proper maintaining of social distancing of the exposed and asymptomatic individuals play key role for controlling the disease. We have validated the model by considering the COVID-19 cases of Italy and the future situations of epidemicity in Italy have been predicted from the model. We have estimated the basic reproduction number for the COVID-19 outbreak in Italy and effective reproduction number has also been studied. Finally, an optimal control model has been formulated and solved to realize the positive impacts of adapting lock down by many countries for maintaining social distancing. |
format | Online Article Text |
id | pubmed-8603917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86039172021-11-22 Mathematical modelling of COVID-19: A case study of Italy Ghosh, Jayanta Kumar Biswas, Sudhanshu Kumar Sarkar, Susmita Ghosh, Uttam Math Comput Simul Original Articles This manuscript describes a mathematical epidemiological model of COVID-19 to investigate the dynamics of this pandemic disease and we have fitted this model to the current COVID-19 cases in Italy. We have obtained the basic reproduction number which plays a crucial role on the stability of disease free equilibrium point. Backward bifurcation with respect to the cure rate of treatment occurs conditionally. It is clear from the sensitivity analysis that the developments of self immunities with proper maintaining of social distancing of the exposed and asymptomatic individuals play key role for controlling the disease. We have validated the model by considering the COVID-19 cases of Italy and the future situations of epidemicity in Italy have been predicted from the model. We have estimated the basic reproduction number for the COVID-19 outbreak in Italy and effective reproduction number has also been studied. Finally, an optimal control model has been formulated and solved to realize the positive impacts of adapting lock down by many countries for maintaining social distancing. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2022-04 2021-11-19 /pmc/articles/PMC8603917/ /pubmed/34840409 http://dx.doi.org/10.1016/j.matcom.2021.11.008 Text en © 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. 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 Articles Ghosh, Jayanta Kumar Biswas, Sudhanshu Kumar Sarkar, Susmita Ghosh, Uttam Mathematical modelling of COVID-19: A case study of Italy |
title | Mathematical modelling of COVID-19: A case study of Italy |
title_full | Mathematical modelling of COVID-19: A case study of Italy |
title_fullStr | Mathematical modelling of COVID-19: A case study of Italy |
title_full_unstemmed | Mathematical modelling of COVID-19: A case study of Italy |
title_short | Mathematical modelling of COVID-19: A case study of Italy |
title_sort | mathematical modelling of covid-19: a case study of italy |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8603917/ https://www.ncbi.nlm.nih.gov/pubmed/34840409 http://dx.doi.org/10.1016/j.matcom.2021.11.008 |
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