Stochastic SIV in-host model of dengue virus transmission

The virus transmission in the host depends upon various fundamental factors such as cellular mortality rates, the production rate of viruses, etc., which change unpredictably in a random environment. From this viewpoint, this paper gives a detailed analysis of a stochastic in-host model of dengue virus transmission. Our main purpose this research work is to analyze an SIV in-host model of the virus transmission in the presence of white noise in every dynamic state. Firstly, a deterministic transmission model is described. Later, it is extended to a stochastic system. The basic reproduction number is computed using the Next Generation Matrix method. The conditions for the extinction and persistence of the disease are also derived. To determine the effect of fluctuations and variations in cell and virus populations in a stochastic model affected by Gaussian white noise, we apply the Fourier transform method. Two distinct equilibrium states are observed and are referred to as virus-free equilibrium and endemic equilibrium state. In addition, for R-0<1, the host is free of infection and the disease will persist if R-0>1. Numerical simulation is carried out, and the results confirm that the system fluctuates in the presence of white noise. Also, it has been observed that in the presence of single nonzero noise intensity, the transmission process shows a random character. The variances of all populations are computed numerically. Variances vary depending on how parameter values change. To assess the impact of model parameters on virus transmission and prevalence, sensitivity analysis is also conducted on the parameters to evaluate their relative importance. Sensitivity analysis implies that the system behaves deterministically when noise intensities are too low. Our findings indicate that the model fluctuates under the presence of noise, which obviously affects initially the transmission of the virus and subsequent spread of infection.