https://doi.org/10.1140/epjp/s13360-023-04633-7
Regular Article
Analysis of a multiply delayed stochastic Ebola model based on probability density function with case study
1
School of Mathematics and Physics, Anqing Normal University, 246001, Anqing, People’s Republic of China
2
Department of Mathematics, Sun Yat-sen University Guangzhou, 510275, Guangzhou, People’s Republic of China
3
Department of Mathematics and Application, Faculty of Sciences and Technology, Hassan II University of Casablanca, PO Box 146, 20650, Mohammedia, Morocco
Received:
21
July
2023
Accepted:
26
October
2023
Published online:
15
November
2023
In this study, we introduce a new version of the SIQC epidemic model, focusing on Ebola infection dynamics and emphasizing time-delay effects. We have demonstrated the existence of a unique solution for the proposed stochastic model through rigorous mathematical derivations. Furthermore, by developing a stochastic Lyapunov function, we assess the extinction and persistence of the proposed stochastic model. We fit the model to available Ebola virus data in Western Guinea from the first forty weeks of the 2015 Ebola outbreak using the conventional curve fitting method, and the model parameters were calculated as a result. To reinforce our findings, we provide computer simulations as supplementary evidence. Based on the simulation findings using the stochastic SIQC model with time delay, it is determined that perturbations and time delay greatly impact the risk of Ebola virus transmission.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
