Stochastic epidemic model for the dynamics of novel coronavirus transmission
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10254846" target="_blank" >RIV/61989100:27740/24:10254846 - isvavai.cz</a>
Result on the web
<a href="https://www.aimspress.com/article/doi/10.3934/math.2024608" target="_blank" >https://www.aimspress.com/article/doi/10.3934/math.2024608</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3934/math.2024608" target="_blank" >10.3934/math.2024608</a>
Alternative languages
Result language
angličtina
Original language name
Stochastic epidemic model for the dynamics of novel coronavirus transmission
Original language description
Stochastic differential equation models are important and provide more valuable outputs to examine the dynamics of SARS-CoV-2 virus transmission than traditional models. SARS-CoV-2 virus transmission is a contagious respiratory disease that produces asymptomatically and symptomatically infected individuals who are susceptible to multiple infections. This work was purposed to introduce an epidemiological model to represent the temporal dynamics of SARS-CoV-2 virus transmission through the use of stochastic differential equations. First, we formulated the model and derived the well-posedness to show that the proposed epidemiological problem is biologically and mathematically feasible. We then calculated the stochastic reproductive parameters for the proposed stochastic epidemiological model and analyzed the model extinction and persistence. Using the stochastic reproductive parameters, we derived the condition for disease extinction and persistence. Applying these conditions, we have performed large-scale numerical simulations to visualize the asymptotic analysis of the model and show the effectiveness of the results derived.
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
—
Continuities
—
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
AIMS Mathematics
ISSN
2473-6988
e-ISSN
2473-6988
Volume of the periodical
9
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
25
Pages from-to
12433-12457
UT code for WoS article
001197002100005
EID of the result in the Scopus database
2-s2.0-85189150905