Abstract

Hepatitis B is a globally infectious disease. It is pretty contagious and can be transmitted by blood or bodily fluids, through things like sharing razors and toothbrushes. It has been called the silent killer because it is asymptomatic, one might have the virus but not know until it manifests itself until much later. Since people do not give attention, it will develop into cirrhosis and hepatocellular carcinoma that leads to liver transplantation and death. This nature of HBV disease motivated us to perform this work. Mathematical modeling of HBV transmission is an interesting research area. In this paper, we present characteristics of HBV virus transmission in the form of a mathematical model. We proposed and analyzed a compartmental nonlinear deterministic mathematical model SEACTR for transmission dynamics and control of hepatitis B virus disease. In this model, we used force infection which takes the contact rate of susceptible population and transmission probability into account. We proved that the solution of the considered dynamical system is positive and bounded. The model is studied qualitatively using the stability theory of differential equations and the effective reproductive number which represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The sensitivity index shows that the transfer rate from exposed class to acute infective class and transfer rate from exposed class to chronic infective class are the most dominant parameters contributing to the transmission of HBV. On the one hand, the vaccination rate and treatment rate are the parameters that suppress the transmission of the disease the most, and enhancing the vaccination rate for newborns and treatment for chronically infected individuals is very effective to stop the transmission of HBV. The combined efforts of vaccination, effective treatment, and interruption of transmission make elimination of the infection plausible and may eventually lead to the eradication of the virus.

Highlights

  • Hepatitis means inflammation of the liver. e liver is a vital organ that processes nutrients, filters blood, and fights infections [1]

  • We study the dynamics of hepatitis B virus (HBV) infection under the administration of vaccination and treatment, where HBV infection is transmitted in two ways through vertical transmission and horizontal transmission

  • As public health policy decisions are becoming more complex in a globalized and digitalized world, the benefits that mathematical models can offer for analyzing problems and quantifying the possible impact of interventions are huge [10]. ese benefits can only be fully reaped, if mathematical modeling is sufficiently supported and facilitated within the organization of public health institutes

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Summary

Introduction

Hepatitis means inflammation of the liver. e liver is a vital organ that processes nutrients, filters blood, and fights infections [1]. Mathematical modeling has a long history and has become an important tool in decision-making for public health in the last two decades in the field of infectious disease control. We study the dynamics of hepatitis B virus (HBV) infection under the administration of vaccination and treatment, where HBV infection is transmitted in two ways through vertical transmission and horizontal transmission. Is work will contribute to understanding which infective class plays more roles in transmitting HBV disease and the collaboration of vaccination and treatment interventions is the best strategy to decrease transmission of the disease. While the horizontal transmission is reduced through the administration of vaccination to those susceptible individuals especially for the new born populations, the vertical transmission gets reduced through the administration of treatment to chronically infected individuals; the vaccine and the treatment play different roles in controlling HBV. Since HBV is an asymptomatic and silent killer, we are motivated to study factors contributing to its transmission and controlling strategies

Model Description and Formulation
Biological Meaning
C δ1 C2
Sensitivity Analysis
Numerical Simulation and Discussion
Conclusion
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