Abstract

An epidemic model with saturated incidence rate and vaccination is investigated. The model exhibits two equilibria namely disease-free and endemic equilibria. It is shown that if the basic reproduction number (R0) is less than unity, the disease-free equilibrium is locally asymptotically stable and in such case, the endemic equilibrium does not exist. Also, it is shown that if R0 > 1, the disease is persistent and the unique endemic equilibrium of the system with saturation incidence is locally asymptotically stable. Lyapunov function and Dulac’s criterion plus Poincare-Bendixson theorem are applied to prove the global stability of the disease-free and endemic equilibria respectively. The effect of vaccine in the model is critically looked into.

Highlights

  • Vaccinating susceptible against disease infections is an effective measure to control and prevent the spread of the infection

  • Lyapunov function and Dulac’s criterion plus Poincare-Bendixson theorem are applied to prove the global stability of the disease-free and endemic equilibria respectively

  • Some of the main findings of this study are: i) The model has a globally-asymptotically stable disease-free equilibrium whenever the associated reproduction number is less than unity; ii) The model has a unique endemic equilibrium under certain conditions

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Summary

Introduction

Vaccinating susceptible against disease infections is an effective measure to control and prevent the spread of the infection. Adebimpe [7] investigated a SEIV epidemic model with saturated incidence rate that incorporates polynomial information on current and past states of the disease. He showed that if the basic reproduction number R0 1 , the Disease-Free Equilibrium (DFE) is locally asymptotically stable and by the use of Lyapunov function, DFE is globally asymptotically stable and in such a case, the Endemic Equilibrium (EE) is unstable. Adebimpe et al [8] investigated the global stability of a SEIR epidemic model with saturating incidence rate They identified a threshold R0 which determines the outcome of the disease.

Local stability of the disease-free equilibrium
Local stability of the endemic equilibrium
Global stability of disease-free equilibrium
Discussion of results
Conclusion

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