Dynamics of COVID-19 mathematical model with stochastic perturbation
Zizhen Zhang, Anwar Zeb, Sultan Hussain, Ebraheem Alzahrani
Abstract
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.
Topics & Concepts
Coronavirus disease 2019 (COVID-19)Ordinary differential equationPerturbation (astronomy)Mathematics2019-20 coronavirus outbreakPartial differential equationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Applied mathematicsStatistical physicsDifferential equationMathematical analysisVirologyPhysicsMedicineInfectious disease (medical specialty)Quantum mechanicsOutbreakPathologyDiseaseCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsMathematical Biology Tumor Growth