The stochastic bifurcation analysis and stochastic delayed optimal control for epidemic model with general incidence function.

In the history of the world, contagious diseases have been proved to pose serious threats to humanity that needs uttermost research in the field and its prompt implementations. With this motive, an attempt has been made to investigate the spread of such contagion by using a delayed stochastic epidemic model with general incidence rate, time-delay transmission, and the concept of cross immunity. It is proved that the system is mathematically and biologically well-posed by showing that there exist a positive and bounded global solution of the model. Necessary conditions are derived, which guarantees the permanence as well as extinction of the disease. The model is further investigated for the existence of an ergodic stationary distribution and established sufficient conditions. The non-zero periodic solution of the stochastic model is analyzed quantitatively. The analysis of optimality and time delay is used, and a proper strategy was presented for prevention of the disease. A scheme for the numerical simulations is developed and implemented in MATLAB, which reflects the long term behavior of the model. Simulation suggests that the noises play a vital role in controlling the spread of an epidemic following the proposed flow, and the case of disease extinction is directly proportional to the magnitude of the white noises. Since time delay reflects the dynamics of recurring epidemics, therefore, it is believed that this study will provide a robust basis for studying the behavior and mechanism of chronic infections.