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 RE 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 RE 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.

Authors

Publication Details

Journal
Scientific African
Published
2025-08-26
DOI
https://doi.org/10.1016/j.sciaf.2025.e02894
Citations
1
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
1.88
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article

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

Maranya Mayengo, Nkuba Nyerere, Farai Nyabadza, Chiganga S. Ruoja
1 citations
Scientific African
Mathematical and Theoretical Epidemiology and Ecology Models
1.88
article

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

Maranya Mayengo, Nkuba Nyerere, Farai Nyabadza, Chiganga S. Ruoja
article en
1 citations

Abstract

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 RE 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 RE 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.

Scientific AfricanVol. 29
Openalex Percentile: Top 13%
Mathematical and Theoretical Epidemiology and Ecology Models
1.88
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Exploring the role of funding-driven vaccination in infection dynamics of TB: A mathematical modeling approach — Maranya Mayengo, Nkuba Nyerere, et al. · Scientific African (2025) | TGRS Research Map | TGRS