Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density
Plant disease incidence rate and impacts can be influenced by viral interactions amongst plant hosts. However, very few mathematical models aim to understand the viral dynamics within plants. In this study, we will analyze the dynamics of two models of virus transmission in plants to incorporate eit...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Applied Mathematics and Statistics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fams.2022.1001392/full |
| _version_ | 1811334363816656896 |
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| author | Nabeela Anwar Shafaq Naz Muhammad Shoaib |
| author_facet | Nabeela Anwar Shafaq Naz Muhammad Shoaib |
| author_sort | Nabeela Anwar |
| collection | DOAJ |
| description | Plant disease incidence rate and impacts can be influenced by viral interactions amongst plant hosts. However, very few mathematical models aim to understand the viral dynamics within plants. In this study, we will analyze the dynamics of two models of virus transmission in plants to incorporate either a time lag or an exposed plant density into the system governed by ODEs. Plant virus propagation model by vector (PVPMV) divided the population into four classes: susceptible plants [S(t)], infectious plants [I(t)], susceptible vectors [X(t)], and infectious vectors [Y(t)]. The approximate solutions for classes S(t), I(t), X(t), and Y(t) are determined by the implementation of exhaustive scenarios with variation in the infection ratio of a susceptible plant by an infected vector, infection ratio of vectors by infected plants, plants' natural fatality rate, plants' increased fatality rate owing to illness, vectors' natural fatality rate, vector replenishment rate, and plants' proliferation rate, numerically by exploiting the knacks of the Adams method (ADM) and backward differentiation formula (BDF). Numerical results and graphical interpretations are portrayed for the analysis of the dynamical behavior of disease by means of variation in physical parameters utilized in the plant virus models. |
| first_indexed | 2024-04-13T17:07:45Z |
| format | Article |
| id | doaj.art-1d0b840755a540e4a573eea0e0ff3a37 |
| institution | Directory Open Access Journal |
| issn | 2297-4687 |
| language | English |
| last_indexed | 2024-04-13T17:07:45Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Applied Mathematics and Statistics |
| spelling | doaj.art-1d0b840755a540e4a573eea0e0ff3a372022-12-22T02:38:25ZengFrontiers Media S.A.Frontiers in Applied Mathematics and Statistics2297-46872022-11-01810.3389/fams.2022.10013921001392Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and densityNabeela Anwar0Shafaq Naz1Muhammad Shoaib2Department of Mathematics, University of Gujrat, Gujrat, PakistanDepartment of Mathematics, University of Gujrat, Gujrat, PakistanDepartment of Mathematics, Commission on Science and Technology for Sustainable Development in the South University Islamabad, Attock, PakistanPlant disease incidence rate and impacts can be influenced by viral interactions amongst plant hosts. However, very few mathematical models aim to understand the viral dynamics within plants. In this study, we will analyze the dynamics of two models of virus transmission in plants to incorporate either a time lag or an exposed plant density into the system governed by ODEs. Plant virus propagation model by vector (PVPMV) divided the population into four classes: susceptible plants [S(t)], infectious plants [I(t)], susceptible vectors [X(t)], and infectious vectors [Y(t)]. The approximate solutions for classes S(t), I(t), X(t), and Y(t) are determined by the implementation of exhaustive scenarios with variation in the infection ratio of a susceptible plant by an infected vector, infection ratio of vectors by infected plants, plants' natural fatality rate, plants' increased fatality rate owing to illness, vectors' natural fatality rate, vector replenishment rate, and plants' proliferation rate, numerically by exploiting the knacks of the Adams method (ADM) and backward differentiation formula (BDF). Numerical results and graphical interpretations are portrayed for the analysis of the dynamical behavior of disease by means of variation in physical parameters utilized in the plant virus models.https://www.frontiersin.org/articles/10.3389/fams.2022.1001392/fullplant virus propagation model by vector (PVPMV)Adams method (ADM)backward differentiation formula (BDF)ordinary differential equations (ODEs)virus transmissiontime lag |
| spellingShingle | Nabeela Anwar Shafaq Naz Muhammad Shoaib Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density Frontiers in Applied Mathematics and Statistics plant virus propagation model by vector (PVPMV) Adams method (ADM) backward differentiation formula (BDF) ordinary differential equations (ODEs) virus transmission time lag |
| title | Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density |
| title_full | Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density |
| title_fullStr | Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density |
| title_full_unstemmed | Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density |
| title_short | Reliable numerical treatment with Adams and BDF methods for plant virus propagation model by vector with impact of time lag and density |
| title_sort | reliable numerical treatment with adams and bdf methods for plant virus propagation model by vector with impact of time lag and density |
| topic | plant virus propagation model by vector (PVPMV) Adams method (ADM) backward differentiation formula (BDF) ordinary differential equations (ODEs) virus transmission time lag |
| url | https://www.frontiersin.org/articles/10.3389/fams.2022.1001392/full |
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