Virulence evolution and behavior game analysis with two strains of viral infectious disease

In this paper, we investigate virulence evolutionary dynamics and game dynamics of behavior in viral infectious diseases. A mutant strain is introduced at the endemic equilibrium of the original strain and to define the fitness function of mutant strain. Adaptive evolution theory is used to establish a virulence evolutionary model, and the relationship between the evolutionary singular strategy and stability of equilibrium is analyzed. We use evolutionary game theory to couple behavior choice with viral infectious diseases. In addition, numerical simulations are carried out to verify theoretical results with COVID-19 data in the United States. The least squares principle is applied to fit the function relationship between transmission rate and virulence. Through results of numerical simulations, it can be concluded that improving perceived risk awareness of infectious diseases can reduce the infection risk in susceptible populations.