article · Computational and Mathematical Methods in Medicine
Co-infection with hepatitis B virus and COVID-19 presents a significant public health challenge in several regions. To examine how protective measures and medical treatments affect community spread, an epidemiological mathematical model of this co-infection was constructed and analysed. The model establishes mathematical boundaries, reproduction numbers, and disease-free equilibrium stability criteria. Findings indicate that transmission rates represent the most influential drivers of disease propagation, and that individual single infections heavily influence the spread of co-infection. Numerical simulations reveal that deploying protective interventions and medical treatments at the same time is the most effective approach to reduce or eradicate dual transmission within a population. Ultimately, managing co-infection depends on prioritising efforts that prevent initial, single infections as well as simultaneous dual infections.
Understanding how two diseases interact within a single population helps health authorities deploy resources efficiently. This mathematical modelling demonstrates that tackling individual hepatitis B and COVID-19 infections directly decreases the burden of severe co-infections. It also confirms that relying on treatment alone is insufficient, proving that concurrent protective and preventative measures are critical to halting transmission.
This theoretical research provides a mathematical framework that could inform public health planning tools or epidemiological decision-support software used by healthcare policymakers and disease control agencies. Because the findings are based entirely on mathematical analyses and numerical simulations, the work is at an early research stage and would require empirical validation and software development before being used in real-world policy design.
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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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DOI: 10.1155/2023/6908757
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