Computational analysis of stochastic delay dynamics in maize streak virus
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10259166" target="_blank" >RIV/61989100:27240/25:10259166 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/25:10259166
Result on the web
<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0337556" target="_blank" >https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0337556</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pone.0337556" target="_blank" >10.1371/journal.pone.0337556</a>
Alternative languages
Result language
angličtina
Original language name
Computational analysis of stochastic delay dynamics in maize streak virus
Original language description
Objectives The primary goal of this research is to analyze the transmission dynamics of Maize Streak Virus (MSV) by means of a computational and stochastic modeling technique where the time delay and uncertainty factors in the epidemic process are vital considerations. Methodology A compartmental MSV deterministic model was established, which later got an extension to a stochastic delay differential system having five biological compartments consisting of susceptible, insecticide-treated, exposed, infected, and recovered plants. Analytical methods were employed to find the maize streak–free and endemic equilibriums and to derive the treatment reproduction number. The stability of the deterministic and stochastic systems was studied. The numerical methods used for comparison were Euler-Maruyama, stochastic Runge–Kutta, and the stochastic Nonstandard Finite Difference (NSFD) scheme, which were assessed for accuracy, stability, and computational efficiency. Key Results Theoretical results show that under some parameter values, both equilibrium points are stable in an asymptotic sense. The numerical experiments reveal that the stochastic NSFD scheme is more stable, preserves positivity better, and is independent of step size than the classical methods. Including the stochasticity captures the uncertainty associated with MSV transmission in the real world, thereby enhancing the predictive simulation’s validity. Conclusions The suggested stochastic NSFD model is indeed a strong computationally efficient and biologically realistic method to simulate MSV and other plant virus epidemics. The results boost our understanding and management of the agricultural disease control strategies.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10100 - Mathematics
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS One
ISSN
1932-6203
e-ISSN
1932-6203
Volume of the periodical
20
Issue of the periodical within the volume
12
Country of publishing house
US - UNITED STATES
Number of pages
28
Pages from-to
"e0337556"
UT code for WoS article
001641398400027
EID of the result in the Scopus database
2-s2.0-105024716050