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A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19
Mitigating the devastating effect of COVID-19 is necessary to control the infectivity and mortality rates. Hence, several strategies such as quarantine of exposed and infected individuals and restricting movement through lockdown of geographical regions have been implemented in most countries. On th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674241/ https://www.ncbi.nlm.nih.gov/pubmed/34912038 http://dx.doi.org/10.1038/s41598-021-03436-z |
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author | Prabakaran, R. Jemimah, Sherlyn Rawat, Puneet Sharma, Divya Gromiha, M. Michael |
author_facet | Prabakaran, R. Jemimah, Sherlyn Rawat, Puneet Sharma, Divya Gromiha, M. Michael |
author_sort | Prabakaran, R. |
collection | PubMed |
description | Mitigating the devastating effect of COVID-19 is necessary to control the infectivity and mortality rates. Hence, several strategies such as quarantine of exposed and infected individuals and restricting movement through lockdown of geographical regions have been implemented in most countries. On the other hand, standard SEIR based mathematical models have been developed to understand the disease dynamics of COVID-19, and the proper inclusion of these restrictions is the rate-limiting step for the success of these models. In this work, we have developed a hybrid Susceptible-Exposed-Infected-Quarantined-Removed (SEIQR) model to explore the influence of quarantine and lockdown on disease propagation dynamics. The model is multi-compartmental, and it considers everyday variations in lockdown regulations, testing rate and quarantine individuals. Our model predicts a considerable difference in reported and actual recovered and deceased cases in qualitative agreement with recent reports. |
format | Online Article Text |
id | pubmed-8674241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86742412021-12-16 A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 Prabakaran, R. Jemimah, Sherlyn Rawat, Puneet Sharma, Divya Gromiha, M. Michael Sci Rep Article Mitigating the devastating effect of COVID-19 is necessary to control the infectivity and mortality rates. Hence, several strategies such as quarantine of exposed and infected individuals and restricting movement through lockdown of geographical regions have been implemented in most countries. On the other hand, standard SEIR based mathematical models have been developed to understand the disease dynamics of COVID-19, and the proper inclusion of these restrictions is the rate-limiting step for the success of these models. In this work, we have developed a hybrid Susceptible-Exposed-Infected-Quarantined-Removed (SEIQR) model to explore the influence of quarantine and lockdown on disease propagation dynamics. The model is multi-compartmental, and it considers everyday variations in lockdown regulations, testing rate and quarantine individuals. Our model predicts a considerable difference in reported and actual recovered and deceased cases in qualitative agreement with recent reports. Nature Publishing Group UK 2021-12-15 /pmc/articles/PMC8674241/ /pubmed/34912038 http://dx.doi.org/10.1038/s41598-021-03436-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Prabakaran, R. Jemimah, Sherlyn Rawat, Puneet Sharma, Divya Gromiha, M. Michael A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title | A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title_full | A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title_fullStr | A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title_full_unstemmed | A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title_short | A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19 |
title_sort | novel hybrid seiqr model incorporating the effect of quarantine and lockdown regulations for covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674241/ https://www.ncbi.nlm.nih.gov/pubmed/34912038 http://dx.doi.org/10.1038/s41598-021-03436-z |
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