Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management
In this paper, a mathematical model based on COVID-19 is developed to study and manage disease outbreaks. The effect of vaccination with regard to its efficacy and percentage of population vaccinated in a closed population is investigated. To study virus transmission, the system employs six nonlinea...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/4/821 |
| _version_ | 1797619532353765376 |
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| author | Charu Arora Poras Khetarpal Saket Gupta Nuzhat Fatema Hasmat Malik Asyraf Afthanorhan |
| author_facet | Charu Arora Poras Khetarpal Saket Gupta Nuzhat Fatema Hasmat Malik Asyraf Afthanorhan |
| author_sort | Charu Arora |
| collection | DOAJ |
| description | In this paper, a mathematical model based on COVID-19 is developed to study and manage disease outbreaks. The effect of vaccination with regard to its efficacy and percentage of population vaccinated in a closed population is investigated. To study virus transmission, the system employs six nonlinear ordinary differential equations with susceptible–exposed–asymptomatic–infected–vaccinated–recovered populations and the basic reproduction number are calculated. The proposed model describes for highly infectious diseases (such as COVID-19) in a closed containment area with no migration. This paper considers that the percentage of vaccinated population has a significant impact on the number of COVID-19 positive cases during the pandemic wave and examines how the pandemic rise time is delayed. Numerical simulation to investigate disease outbreaks when the community is undergoing vaccination is performed, taking the efficacy rate of the vaccine into account. Sensitivity Index values are calculated for the reproduction number and their relations with few other parameters are depicted. |
| first_indexed | 2024-03-11T08:28:21Z |
| format | Article |
| id | doaj.art-64092ab712634ae3a334a982b3805424 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T08:28:21Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-64092ab712634ae3a334a982b38054242023-11-16T21:54:29ZengMDPI AGMathematics2227-73902023-02-0111482110.3390/math11040821Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases ManagementCharu Arora0Poras Khetarpal1Saket Gupta2Nuzhat Fatema3Hasmat Malik4Asyraf Afthanorhan5Department of Applied Sciences, Bharati Vidyapeeth’s College of Engineering, Delhi 110063, IndiaDepartment of Information Technology, Bharati Vidyapeeth’s College of Engineering, Delhi 110063, IndiaDepartment of Instrumentation and Control Engineering, Bharati Vidyapeeth’s College of Engineering, Delhi 110063, IndiaFaculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, MalaysiaDepartment of Electrical Power Engineering, Faculty of Electrical Engineering, University Technology Malaysia (UTM), Johor Bahru 81310, Johor, MalaysiaFaculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, MalaysiaIn this paper, a mathematical model based on COVID-19 is developed to study and manage disease outbreaks. The effect of vaccination with regard to its efficacy and percentage of population vaccinated in a closed population is investigated. To study virus transmission, the system employs six nonlinear ordinary differential equations with susceptible–exposed–asymptomatic–infected–vaccinated–recovered populations and the basic reproduction number are calculated. The proposed model describes for highly infectious diseases (such as COVID-19) in a closed containment area with no migration. This paper considers that the percentage of vaccinated population has a significant impact on the number of COVID-19 positive cases during the pandemic wave and examines how the pandemic rise time is delayed. Numerical simulation to investigate disease outbreaks when the community is undergoing vaccination is performed, taking the efficacy rate of the vaccine into account. Sensitivity Index values are calculated for the reproduction number and their relations with few other parameters are depicted.https://www.mdpi.com/2227-7390/11/4/821COVID-19modified SEAIR modeldisease outbreakhuman vaccination |
| spellingShingle | Charu Arora Poras Khetarpal Saket Gupta Nuzhat Fatema Hasmat Malik Asyraf Afthanorhan Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management Mathematics COVID-19 modified SEAIR model disease outbreak human vaccination |
| title | Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management |
| title_full | Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management |
| title_fullStr | Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management |
| title_full_unstemmed | Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management |
| title_short | Mathematical Modelling to Predict the Effect of Vaccination on Delay and Rise of COVID-19 Cases Management |
| title_sort | mathematical modelling to predict the effect of vaccination on delay and rise of covid 19 cases management |
| topic | COVID-19 modified SEAIR model disease outbreak human vaccination |
| url | https://www.mdpi.com/2227-7390/11/4/821 |
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