Exploring the role of funding-driven vaccination in infection dynamics of TB: A mathematical modeling approach

This study explores the impact of funding-driven vaccination on the transmission and spread of tuberculosis within the human population. To accurately capture the human behavior, a deterministic mathematical model is formulated, incorporating attitudes of patients towards hospital treatment. The well-posedness of the model is examined using the Lipschitz condition. An effective funding reproduction number $R_E$ is derived via the next-generation matrix method. Model parameters for simulation reasons are estimated by fitting to real-world data. Both theoretical and numerical findings show that $R_E$ decreases with increased vaccination funding and a higher proportion of patients exhibiting positive attitudes towards hospital treatment. These findings underscore the importance for policymakers to prioritize health by ensuring sufficient funding for vaccination programs, which is crucial for reducing disease burden in the community.