Dynamic Analysis of Nonlinear Stochastic ROTA Virus Epidemic Model

Rotavirus is an entirely transmissible virus that causes diarrhea. It has the ability to weather to attribute to the pathogens’ various modes of communication. Worldwide, toddlers and youngsters are especially stricken by rotavirus-precipitated diarrhea. Several rotavirus vaccines have been developed to manage this epidemic. At some point during the outbreak of a disorder, the media plays a critical role. We investigated the impact of the media at various stages of rotavirus vaccination by proposing a deterministic mathematical model. The proposed rotavirus model is characterized into four parts: susceptible (S), vaccinated (V), infected (I), and recovered (R). Basic essential mathematical properties of the model such as positivity and boundedness of solutions, equilibria and their stability are analysed for the deterministic model. We also derived a basic reproduction number to illustrate the epidemiological status of the proposed system. Stability analysis techniques are used to determine the effects of model parameters on the basic reproduction number and symptomatic infected individuals during vaccination. The stochastic model of the proposed system is also developed to capture the variation or uncertainty detected during disease transmission. We solve the stochastic model numerically using Euler Maruyama method. In the stochastic model, the variability in the infected population is found. We observed the variability in the infective population and found their distribution at a particular fixed time, showing that white noise will play an essential role for small populations.