Cargando…

SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman

The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is al...

Descripción completa

Detalles Bibliográficos
Autores principales: Varghese, Abraham, Kolamban, Shajidmon, Sherimon, Vinu, Lacap, Eduardo M., Ahmed, Saad Salman, Sreedhar, Jagath Prasad, Al Harthi, Hasina, Al Shuaily, Huda Salim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184795/
https://www.ncbi.nlm.nih.gov/pubmed/34099741
http://dx.doi.org/10.1038/s41598-021-91114-5
_version_ 1783704652284428288
author Varghese, Abraham
Kolamban, Shajidmon
Sherimon, Vinu
Lacap, Eduardo M.
Ahmed, Saad Salman
Sreedhar, Jagath Prasad
Al Harthi, Hasina
Al Shuaily, Huda Salim
author_facet Varghese, Abraham
Kolamban, Shajidmon
Sherimon, Vinu
Lacap, Eduardo M.
Ahmed, Saad Salman
Sreedhar, Jagath Prasad
Al Harthi, Hasina
Al Shuaily, Huda Salim
author_sort Varghese, Abraham
collection PubMed
description The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an adequate description of the transmission of any disease. In this research work, we have formulated a deterministic compartmental model (SEAMHCRD) including various stages of infection, such as Mild, Moderate, Severe and Critical to study the spreading of COVID-19 and estimated the model parameters by fitting the model with the reported data of ongoing pandemic in Oman. The steady-state, stability and final pandemic size of the model has been proved mathematically. The various transmission as well as transition parameters are estimated during the period from June 4th to July 30th, 2020. Based on the currently estimated parameters, the pandemic size is also predicted for another 100 days. Sensitivity analysis is performed to identify the key model parameters, and the parameter gamma due to contact with the symptomatic moderately infected is found to be more significant in spreading the disease. Accordingly, the corresponding basic reproduction number has also been computed using the Next Generation Matrix (NGM) method. As the value of the basic reproduction number (R(0)) is 0.9761 during the period from June 4th to July 30th, 2020, the disease-free equilibrium is stable. Isolation and tracing the contact of infected individuals are recommended to control the spread of disease.
format Online
Article
Text
id pubmed-8184795
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-81847952021-06-08 SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman Varghese, Abraham Kolamban, Shajidmon Sherimon, Vinu Lacap, Eduardo M. Ahmed, Saad Salman Sreedhar, Jagath Prasad Al Harthi, Hasina Al Shuaily, Huda Salim Sci Rep Article The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an adequate description of the transmission of any disease. In this research work, we have formulated a deterministic compartmental model (SEAMHCRD) including various stages of infection, such as Mild, Moderate, Severe and Critical to study the spreading of COVID-19 and estimated the model parameters by fitting the model with the reported data of ongoing pandemic in Oman. The steady-state, stability and final pandemic size of the model has been proved mathematically. The various transmission as well as transition parameters are estimated during the period from June 4th to July 30th, 2020. Based on the currently estimated parameters, the pandemic size is also predicted for another 100 days. Sensitivity analysis is performed to identify the key model parameters, and the parameter gamma due to contact with the symptomatic moderately infected is found to be more significant in spreading the disease. Accordingly, the corresponding basic reproduction number has also been computed using the Next Generation Matrix (NGM) method. As the value of the basic reproduction number (R(0)) is 0.9761 during the period from June 4th to July 30th, 2020, the disease-free equilibrium is stable. Isolation and tracing the contact of infected individuals are recommended to control the spread of disease. Nature Publishing Group UK 2021-06-07 /pmc/articles/PMC8184795/ /pubmed/34099741 http://dx.doi.org/10.1038/s41598-021-91114-5 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
Varghese, Abraham
Kolamban, Shajidmon
Sherimon, Vinu
Lacap, Eduardo M.
Ahmed, Saad Salman
Sreedhar, Jagath Prasad
Al Harthi, Hasina
Al Shuaily, Huda Salim
SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title_full SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title_fullStr SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title_full_unstemmed SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title_short SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman
title_sort seamhcrd deterministic compartmental model based on clinical stages of infection for covid-19 pandemic in sultanate of oman
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184795/
https://www.ncbi.nlm.nih.gov/pubmed/34099741
http://dx.doi.org/10.1038/s41598-021-91114-5
work_keys_str_mv AT vargheseabraham seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT kolambanshajidmon seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT sherimonvinu seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT lacapeduardom seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT ahmedsaadsalman seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT sreedharjagathprasad seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT alharthihasina seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman
AT alshuailyhudasalim seamhcrddeterministiccompartmentalmodelbasedonclinicalstagesofinfectionforcovid19pandemicinsultanateofoman