Evidence map›Paper›PMID 36560391›Full record

ArticleVaccines2022

A Mathematical Model of Vaccinations Using New Fractional Order Derivative.

Asma, Mehreen Yousaf, Muhammad Afzaal, Mahmoud H DarAssi, Muhammad Altaf Khan, Mohammad Y Alshahrani, Muath Suliman

Abstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

AsmaDepartment of Mathematics, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, Pakistan.
Mehreen YousafDHQ Teaching Hospital, Sahiwal 57000, Punjab, Pakistan.
Muhammad AfzaalLahore General Hospital, Lahore 54000, Punjab, Pakistan.
Mahmoud H DarAssiDepartment of Basic Sciences, Princess Sumaya University for Technology, Amman 11941, Jordan.ORCID 0000-0003-1993-7859
Muhammad Altaf KhanInstitute for Ground Water Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9301, South Africa.ORCID 0000-0002-4483-7879
Mohammad Y AlshahraniDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, P.O. Box 61413, Abha 9088, Saudi Arabia.ORCID 0000-0002-7096-0221
Muath SulimanDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, P.O. Box 61413, Abha 9088, Saudi Arabia.ORCID 0000-0001-6638-2433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This paper studies a simple SVIR (susceptible, vaccinated, infected, recovered) type of model to investigate the coronavirus’s dynamics in Saudi Arabia with the recent cases of the coronavirus. Our purpose is to investigate coronavirus cases in Saudi Arabia and to predict the early eliminations as well as future case predictions. The impact of vaccinations on COVID-19 is also analyzed. Methods: We consider the recently introduced fractional derivative known as the generalized Hattaf fractional derivative to extend our COVID-19 model. To obtain the fitted and estimated values of the parameters, we consider the nonlinear least square fitting method. We present the numerical scheme using the newly introduced fractional operator for the graphical solution of the generalized fractional differential equation in the sense of the Hattaf fractional derivative. Mathematical as well as numerical aspects of the model are investigated. Results: The local stability of the model at disease-free equilibrium is shown. Further, we consider real cases from Saudi Arabia since 1 May−4 August 2022, to parameterize the model and obtain the basic reproduction number R0v≈2.92. Further, we find the equilibrium point of the endemic state and observe the possibility of the backward bifurcation for the model and present their results. We present the global stability of the model at the endemic case, which we found to be globally asymptotically stable when R0v>1. Conclusion: The simulation results using the recently introduced scheme are obtained and discussed in detail. We present graphical results with different fractional orders and found that when the order is decreased, the number of cases decreases. The sensitive parameters indicate that future infected cases decrease faster if face masks, social distancing, vaccination, etc., are effective.

Indexed as

backward bifurcationgeneralized fractional derivativenumerical resultsreal cases

Identifiers

PMID36560391
PMCPMC9785217

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.