A comparative study of deterministic and stochastic computational modeling approaches for analyzing and optimizing COVID-19 control

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10257692" target="_blank" >RIV/61989100:27740/25:10257692 - isvavai.cz</a>

Result on the web

<a href="https://www.nature.com/articles/s41598-025-96127-y" target="_blank" >https://www.nature.com/articles/s41598-025-96127-y</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-025-96127-y" target="_blank" >10.1038/s41598-025-96127-y</a>

Result language

angličtina

Original language name

A comparative study of deterministic and stochastic computational modeling approaches for analyzing and optimizing COVID-19 control

Original language description

This paper presents a comparative analysis of deterministic and stochastic computational modeling approaches for the optimal control of COVID-19. We formulate a compartmental epidemic model with perturbation by white noise that incorporates various factors influencing disease transmission. By incorporating stochastic effects, the model accounts for uncertainties inherent in real-world epidemic data. We establish the mathematical properties of the model, such as well-posedness and the existence of stationary distributions, which are crucial for understanding long-term epidemic dynamics. Moreover, the study presents an optimal control strategies to mitigate the epidemic&apos;s impact, both in deterministic and stochastic sceneries. Reported data from Algeria are used to parameterize the model, ensuring its relevance and applicability to practical satiation. Through numerical simulations, the study provides insights into the effectiveness of different control measures in managing COVID-19 outbreaks. This research contributes to advancing our understanding of epidemic dynamics and informs decision-making processes for epidemic controlling interventions.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10300 - Physical sciences

Project

—

Continuities

O - Projekt operacniho programu

Publication year

2025

Confidentiality

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

Name of the periodical

Scientific Reports

ISSN

2045-2322

e-ISSN

2045-2322

Volume of the periodical

15

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

22

Pages from-to

11710

UT code for WoS article

001460349000016

EID of the result in the Scopus database

2-s2.0-105003260810