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Stationary distribution and density function analysis of stochastic susceptible‐vaccinated‐infected‐recovered (SVIR) epidemic model with vaccination of newborns

Yucong Dai, Baoquan Zhou, Daqing Jiang, Tasawar Hayat

2021Mathematical Methods in the Applied Sciences17 citationsDOI

Abstract

Birth vaccinations are becoming more common in society. In this paper, we describe the developed stochastic susceptible‐vaccinated‐infected‐recovered (SVIR) epidemic model with vaccination of newborns that enable us to concern the stationary distribution and further density function. By constructing a series suitable Lyapunov function, we derive the sufficient conditions of the existence and uniqueness of an ergodic stationary distribution. More importantly, under the same conditions, we creatively find further the density function which is based on solving corresponding Fokker–Planck equation. The results of numerical simulation, which is supported by pertussis disease data, show that our conclusion accords with reality. The density function throws light on the property of an epidemic after being stationary and furnishes more information about the disease.

Topics & Concepts

Stationary distributionUniquenessProbability density functionMathematicsLyapunov functionErgodic theoryVaccinationEpidemic modelApplied mathematicsFunction (biology)Property (philosophy)Distribution (mathematics)Statistical physicsMathematical analysisMedicineStatisticsVirologyPhysicsBiologyEnvironmental healthMarkov chainNonlinear systemPhilosophyEpistemologyPopulationEvolutionary biologyQuantum mechanicsMathematical and Theoretical Epidemiology and Ecology ModelsCOVID-19 epidemiological studiesEvolution and Genetic Dynamics
Stationary distribution and density function analysis of stochastic susceptible‐vaccinated‐infected‐recovered (SVIR) epidemic model with vaccination of newborns | Litcius