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Impact of optimal vaccination and social distancing on COVID-19 pandemic
The first COVID-19 case was reported at Wuhan in China at the end of December 2019 but till today the virus has caused millions of deaths worldwide. Governments of each country, observing the severity, took non-pharmaceutical interventions from the very beginning to break the chain of higher transmi...
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/PMC9056068/ https://www.ncbi.nlm.nih.gov/pubmed/35531464 http://dx.doi.org/10.1016/j.matcom.2022.04.025 |
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author | Saha, Sangeeta Samanta, Guruprasad Nieto, Juan J. |
author_facet | Saha, Sangeeta Samanta, Guruprasad Nieto, Juan J. |
author_sort | Saha, Sangeeta |
collection | PubMed |
description | The first COVID-19 case was reported at Wuhan in China at the end of December 2019 but till today the virus has caused millions of deaths worldwide. Governments of each country, observing the severity, took non-pharmaceutical interventions from the very beginning to break the chain of higher transmission. Fortunately, vaccines are available now in most countries and people are asked to take recommended vaccines as precautionary measures. In this work, an epidemiological model on COVID-19 is proposed where people from the susceptible and asymptomatically infected phase move to the vaccinated class after a full two-dose vaccination. The overall analysis says that the disease transmission rate from symptomatically infected people is most sensitive on the disease prevalence. Moreover, better disease control can be achieved by vaccination of the susceptible class. In the later part of the work, a corresponding optimal control problem is considered where maintaining social distancing and vaccination procedure change with time. The result says that even in absence of social distancing, only the vaccination to people can significantly reduce the overall infected population. From the analysis, it is observed that maintaining physical distancing and taking vaccines at an early stage decreases the infection level significantly in the environment by reducing the probability of becoming infected. |
format | Online Article Text |
id | pubmed-9056068 |
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-90560682022-05-02 Impact of optimal vaccination and social distancing on COVID-19 pandemic Saha, Sangeeta Samanta, Guruprasad Nieto, Juan J. Math Comput Simul Original Articles The first COVID-19 case was reported at Wuhan in China at the end of December 2019 but till today the virus has caused millions of deaths worldwide. Governments of each country, observing the severity, took non-pharmaceutical interventions from the very beginning to break the chain of higher transmission. Fortunately, vaccines are available now in most countries and people are asked to take recommended vaccines as precautionary measures. In this work, an epidemiological model on COVID-19 is proposed where people from the susceptible and asymptomatically infected phase move to the vaccinated class after a full two-dose vaccination. The overall analysis says that the disease transmission rate from symptomatically infected people is most sensitive on the disease prevalence. Moreover, better disease control can be achieved by vaccination of the susceptible class. In the later part of the work, a corresponding optimal control problem is considered where maintaining social distancing and vaccination procedure change with time. The result says that even in absence of social distancing, only the vaccination to people can significantly reduce the overall infected population. From the analysis, it is observed that maintaining physical distancing and taking vaccines at an early stage decreases the infection level significantly in the environment by reducing the probability of becoming infected. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2022-10 2022-04-30 /pmc/articles/PMC9056068/ /pubmed/35531464 http://dx.doi.org/10.1016/j.matcom.2022.04.025 Text en © 2022 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 Saha, Sangeeta Samanta, Guruprasad Nieto, Juan J. Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title | Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title_full | Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title_fullStr | Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title_full_unstemmed | Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title_short | Impact of optimal vaccination and social distancing on COVID-19 pandemic |
title_sort | impact of optimal vaccination and social distancing on covid-19 pandemic |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9056068/ https://www.ncbi.nlm.nih.gov/pubmed/35531464 http://dx.doi.org/10.1016/j.matcom.2022.04.025 |
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