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
2023
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| Online Access: | http://eprints.utm.my/105670/1/HasmatMalik2023_MathematicalModellingtoPredicttheEffect.pdf |
| _version_ | 1811132180012728320 |
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| author | Charu Arora, Charu Arora Poras Khetarpal, Poras Khetarpal Saket Gupta, Saket Gupta Nuzhat Fatema, Nuzhat Fatema Malik, Hasmat Afthanorhan, Asyraf |
| author_facet | Charu Arora, Charu Arora Poras Khetarpal, Poras Khetarpal Saket Gupta, Saket Gupta Nuzhat Fatema, Nuzhat Fatema Malik, Hasmat Afthanorhan, Asyraf |
| author_sort | Charu Arora, Charu Arora |
| collection | ePrints |
| 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 | 2024-09-23T23:59:15Z |
| format | Article |
| id | utm.eprints-105670 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-09-23T23:59:15Z |
| publishDate | 2023 |
| publisher | MDPI |
| record_format | dspace |
| spelling | utm.eprints-1056702024-05-13T07:00:29Z http://eprints.utm.my/105670/ Mathematical modelling to predict the effect of vaccination on delay and rise of COVID-19 cases management Charu Arora, Charu Arora Poras Khetarpal, Poras Khetarpal Saket Gupta, Saket Gupta Nuzhat Fatema, Nuzhat Fatema Malik, Hasmat Afthanorhan, Asyraf Q Science (General) T Technology (General) TK Electrical engineering. Electronics Nuclear engineering 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. MDPI 2023-02 Article PeerReviewed application/pdf en http://eprints.utm.my/105670/1/HasmatMalik2023_MathematicalModellingtoPredicttheEffect.pdf Charu Arora, Charu Arora and Poras Khetarpal, Poras Khetarpal and Saket Gupta, Saket Gupta and Nuzhat Fatema, Nuzhat Fatema and Malik, Hasmat and Afthanorhan, Asyraf (2023) Mathematical modelling to predict the effect of vaccination on delay and rise of COVID-19 cases management. Mathematics, 11 (4). pp. 1-15. ISSN 2227-7390 http://dx.doi.org/10.3390/math11040821 DOI:10.3390/math11040821 |
| spellingShingle | Q Science (General) T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Charu Arora, Charu Arora Poras Khetarpal, Poras Khetarpal Saket Gupta, Saket Gupta Nuzhat Fatema, Nuzhat Fatema Malik, Hasmat Afthanorhan, Asyraf Mathematical modelling to predict the effect of vaccination on delay and rise of COVID-19 cases management |
| 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 | Q Science (General) T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/105670/1/HasmatMalik2023_MathematicalModellingtoPredicttheEffect.pdf |
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