Dynamics of COVID-19 mathematical model with stochastic perturbation

Acknowledging many effects on humans, which are ignored in deterministic models for COVID-19, in this paper, we consider stochastic mathematical model for COVID-19. Firstly, the formulation of a stochastic susceptible–infected–recovered model is presented. Secondly, we devote with full strength our...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Advances in difference equations 2020-08, Vol.2020 (1), p.451-451, Article 451
Hauptverfasser:	Zhang, Zizhen, Zeb, Anwar, Hussain, Sultan, Alzahrani, Ebraheem
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Computer simulation Coronaviruses COVID-19 Difference and Functional Equations Extinction Functional Analysis Itô’s formula Mathematical analysis Mathematical models Mathematical Models of Infectious Diseases Mathematics Mathematics and Statistics Numerical analysis Ordinary Differential Equations Partial Differential Equations Persistence Perturbation methods Stochastic COVID-19 model
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	Acknowledging many effects on humans, which are ignored in deterministic models for COVID-19, in this paper, we consider stochastic mathematical model for COVID-19. Firstly, the formulation of a stochastic susceptible–infected–recovered model is presented. Secondly, we devote with full strength our concentrated attention to sufficient conditions for extinction and persistence. Thirdly, we examine the threshold of the proposed stochastic COVID-19 model, when noise is small or large. Finally, we show the numerical simulations graphically using MATLAB.
ISSN:	1687-1847 1687-1839 1687-1847
DOI:	10.1186/s13662-020-02909-1