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. 2023 Sep 29:2023:6908757.
doi: 10.1155/2023/6908757. eCollection 2023.

Analysis of HBV and COVID-19 Coinfection Model with Intervention Strategies

Shewafera Wondimagegnhu Teklu  1
Affiliations

Analysis of HBV and COVID-19 Coinfection Model with Intervention Strategies

Shewafera Wondimagegnhu Teklu. Comput Math Methods Med. .

Abstract

Coinfection of hepatitis B virus (HBV) and COVID-19 is a common public health problem throughout some nations in the world. In this study, a mathematical model for hepatitis B virus (HBV) and COVID-19 coinfection is constructed to investigate the effect of protection and treatment mechanisms on its spread in the community. Necessary conditions of the proposed model nonnegativity and boundedness of solutions are analyzed. We calculated the model reproduction numbers and carried out the local stabilities of disease-free equilibrium points whenever the associated reproduction number is less than unity. Using the well-known Castillo-Chavez criteria, the disease-free equilibrium points are shown to be globally asymptotically stable whenever the associated reproduction number is less than unity. Sensitivity analysis proved that the most influential parameters are transmission rates. Moreover, we carried out numerical simulation and shown results: some parameters have high spreading effect on the disease transmission, single infections have great impact on the coinfection transmission, and using protections and treatments simultaneously is the most effective strategy to minimize and also to eradicate the HBV and COVID-19 coinfection spreading in the community. It is concluded that to control the transmission of both diseases in a population, efforts must be geared towards preventing incident infection with either or both diseases.

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Conflict of interest statement

The authors declare that they have no conflicts of interest

Figures

Figure 1
Figure 1
The flow chart of the coinfection of HBV and COVID-19 spreading dynamics with λH(t) and λC(t) given in (1) and (2), respectively.
Figure 2
Figure 2
Simulation of sensitivity indices of the model parameters with respect to ℛHC0.
Figure 3
Figure 3
Convergence of the complete coinfection dynamics (3) solutions at ℛHC0 = 0.26 < 1.
Figure 4
Figure 4
Convergence of the complete coinfection dynamics (3) solutions at ℛHC0 = 3.23 > 1.
Figure 5
Figure 5
Impact of σ1 on C.
Figure 6
Figure 6
Impact of σ2 on C.
Figure 7
Figure 7
Impact of γ on HI.
Figure 8
Figure 8
Impact of θ on C.
Figure 9
Figure 9
Impact of σ1 on ℛH.
Figure 10
Figure 10
Impact of γ2 on ℛH.
Figure 11
Figure 11
Impact of γ on ℛH.
Figure 12
Figure 12
Impact of σ2 on ℛC.
Figure 13
Figure 13
Impact of γ1 on ℛC.
Figure 14
Figure 14
Impact of κ on ℛC.
See this image and copyright information in PMC

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