The analysis of the sensitivity of vaccination parameters in a tuberculosis transmission model
Abstract
Tuberculosis (TB) is one of the most dangerous infectious diseases that caused 1,5 million people died from TB in 2018 (including 251.000 people with HIV). As the preventive strategy for the spread of TB, we can use BCG vaccination. This study aims to investigate and analyze the sensitivity of vaccination parameters (to newborns and adults). This model divided the human population into five classes: susceptible , vaccinated , high-risk and low-risk latent, and infectious . Analysis of the mathematical model was discussed by finding the existence and analyzing the model equilibrium's stability based on the Basic Reproduction Number ( ). Furthermore, we determined the sensitivity analysis of the proportion of vaccine and other parameters that affect the TB transmission model. The numerical experiment shows that vaccination to adults more effective than newborns.
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Brauer, F., & Castillo-ChavezCarlos. (2012). Mathematical models in population biology and epidemiology (2nd Ed). Springer.
Centers for Disease Control and Prevention (CDC). (2020). Latent TB infection and TB disease. https://www.cdc.gov/tb/topic/basics/tbinfectiondisease.htm
Choi, S., Jung, E., & Lee, S. M. (2015). Optimal intervention strategy for prevention tuberculosis using a smoking-tuberculosis model. Journal of Theoretical Biology, 380. https://doi.org/10.1016/j.jtbi.2015.05.022
Department of Health and Human Services. (2016). Management, control and prevention of tuberculosis. Melbourne Department of Health and Human Services.
Diekmann, O., Heesterbeek, J. A. P., & Roberts, M. G. (2010). The construction of next-generation matrices for compartmental epidemic models. Journal of the Royal Society Interface, 7(47). https://doi.org/10.1098/rsif.2009.0386
Grange, J. M., Brunet, L. R., & Rieder, H. L. (2011). Immune protection against tuberculosis - When is immunotherapy preferable to vaccination? Tuberculosis, 91(2), 179–185. https://doi.org/10.1016/j.tube.2010.12.004
Hethcote, H. W. (2000). Mathematics of infectious diseases. SIAM Review, 42(4), 599–653. https://doi.org/10.1137/S0036144500371907
Houben, R. M. G. J., & Dodd, P. J. (2016). The Global Burden of Latent Tuberculosis Infection: A Re-estimation Using Mathematical Modelling. PLoS Medicine, 13(10). https://doi.org/10.1371/journal.pmed.1002152
Kim, S., de los Reyes, A. A., & Jung, E. (2018). Mathematical model and intervention strategies for mitigating tuberculosis in the Philippines. Journal of Theoretical Biology, 443. https://doi.org/10.1016/j.jtbi.2018.01.026
Liu, S., Li, Y., Bi, Y., & Huang, Q. (2017). Mixed vaccination strategy for the control of tuberculosis: A case study in China. Mathematical Biosciences and Engineering, 14(3). https://doi.org/10.3934/mbe.2017039
Mishra, B. K., & Srivastava, J. (2014). Mathematical model on pulmonary and multidrug-resistant tuberculosis patients with vaccination. Journal of the Egyptian Mathematical Society, 22(2). https://doi.org/10.1016/j.joems.2013.07.006
Nguipdop-Djomo, P., Heldal, E., Rodrigues, L. C., Abubakar, I., & Mangtani, P. (2016). Duration of BCG protection against tuberculosis and change in effectiveness with time since vaccination in norway: A retrospective population-based cohort study. THE LANCET Infectious Diseases, 16(12), 219–226. https://doi.org/https://doi.org/10.1016/S1473-3099(15)00400-4
Nyabadza, F., & Kgosimore, M. (2012). Modeling the Dynamics of Tuberculosis Transmission in Children and Adults. Journal of Mathematics and Statistics, 8(2). https://doi.org/10.3844/jmssp.2012.229.240
Petruccioli, E., Scriba, T. J., Petrone, L., Hatherill, M., Cirillo, D. M., Joosten, S. A., Ottenhoff, T. H., Denkinger, C. M., & Goletti, D. (2016). Correlates of tuberculosis risk: Predictive biomarkers for progression to active tuberculosis. In European Respiratory Journal (Vol. 48, Issue 6). https://doi.org/10.1183/13993003.01012-2016
Van Den Driessche, P., & Watmough, J. (2002). Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences, 180(1–2). https://doi.org/10.1016/S0025-5564(02)00108-6
World Health Organization (WHO). (2019). Tuberculosis. https://www.who.int/news-room/fact-sheets/detail/tuberculosis
Yang, Y., Tang, S., Ren, X., Zhao, H., & Guo, C. (2016). Global stability and optimal control for a tuberculosis model with vaccination and treatment. Discrete and Continuous Dynamical Systems - Series B, 21(3). https://doi.org/10.3934/dcdsb.2016.21.1009
DOI: http://dx.doi.org/10.24042/djm.v4i1.7116
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