Bifurcation and optimal control for an infectious disease model with the impact of information

A nonlinear infectious disease model with information-influenced vaccination behavior and contact patterns is proposed in this paper, and the impact of information related to disease prevalence on increasing vaccination coverage and reducing disease incidence during the outbreak is considered. First, we perform the analysis for the existence of equilibria and the stability properties of the proposed model. In particular, the geometric approach is used to obtain the sufficient condition which guarantees the global asymptotic stability of the unique endemic equilibrium E-e when the basic reproduction number R-0 > 1. Second, mathematical derivation combined with numerical simulation shows the existence of the double Hopf bifurcation around E-e. Third, based on the numerical results, it is shown that the information coverage and the average information delay may lead to more complex dynamical behaviors. Finally, the optimal control problem is established with information-influenced vaccination and treatment as control variables. The corresponding optimal paths are obtained analytically by using Pontryagin's maximum principle, and the applicability and validity of virous intervention strategies for the proposed controls are presented by numerical experiments.

Automated summary

In this paper, a nonlinear infectious disease model is proposed to consider the impact of information on vaccination behavior and contact patterns. The existence of equilibria and stability properties of the model are analyzed using a geometric approach. The double Hopf bifurcation around the endemic equilibrium is shown through mathematical derivation and numerical simulation. The optimal control problem is established and solved using Pontryagin's maximum principle, and the effectiveness of the proposed control strategies is demonstrated through numerical experiments.