Stochastic epidemic model for the dynamics of novel coronavirus transmission

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Stochastic epidemic model for the dynamics of novel coronavirus transmission

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Stochastic epidemic model for the dynamics of novel coronavirus transmission

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10100 - Mathematics

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

AIMS Mathematics

ISSN

2473-6988

e-ISSN

2473-6988

Svazek periodika

9

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

25

Strana od-do

12433-12457

Kód UT WoS článku

001197002100005

EID výsledku v databázi Scopus

2-s2.0-85189150905