A Within-host Tuberculosis Model Using Optimal Control

Yudi Ari Adi

Abstract


 

In this paper, we studied a mathematical model of tuberculosis with vaccination for the treatment of  tuberculosis. We considered an in-host tuberculosis model that described the interaction between Macrophages and Mycobacterium tuberculosis and investigated the effect of vaccination treatments on uninfected macrophages. Optimal control is applied to show the optimal vaccination and effective strategies to control the disease. The optimal control formula is obtained using the Hamiltonian function and Pontryagin's maximum principle. Finally, we perform numerical simulations to support the analytical results. The results suggest that control or vaccination is required if the maximal transmission of infection rate at which macrophages became infected is large.

 

In this paper, we studied a mathematical model of tuberculosis with vaccination for the treatment of  tuberculosis.We considered an in-host tuberculosis model that described the interaction between macrophages Macrophages and Mycobacterium tuberculosis and investigated the effect of vaccination treatments on uninfected macrophages. Optimal controlis applied to show the optimal vaccination and effective strategies to control the disease. The optimal control formula isobtained using the Hamiltonian function and Pontryagin's maximum principle. Finally, we perform numerical simulations to support the analytical results.The results suggest thatcontrol or vaccination is required if the maximal transmission of infection rate at which macrophages became infected is large.


Keywords


Tuberculosis; Mathematical model; Optimal control; Hamiltonian and Pontryagin function.

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References


Adi, Y. A., & Thobirin, A. (2020). Backward bifurcation in a within-host tuberculosis model. Advances in Mathematics: Scientific Journal. https://doi.org/10.37418/amsj.9.9.76

Agusto, F. B., & Adekunle, A. I. (2014). Optimal control of a two-strain tuberculosis-HIV/AIDS co-infection model. BioSystems. https://doi.org/10.1016/j.biosystems.2014.03.006

Baba, I. A., Abdulkadir, R. A., & Esmaili, P. (2020). Analysis of tuberculosis model with saturated incidence rate and optimal control. Physica A: Statistical Mechanics and Its Applications. https://doi.org/10.1016/j.physa.2019.123237

Becker, R. A., Sierstad, A., Sydsæter, K., & Sydsaeter, K. (1989). Optimal Control Theory with Economic Applications. The Scandinavian Journal of Economics. https://doi.org/10.2307/3440172

Blaser, N., Zahnd, C., Hermans, S., Salazar-Vizcaya, L., Estill, J., Morrow, C., Egger, M., Keiser, O., & Wood, R. (2016). Tuberculosis in Cape Town: An age-structured transmission model. Epidemics. https://doi.org/10.1016/j.epidem.2015.10.001

Bowong, S. (2010). Optimal control of the transmission dynamics of tuberculosis. Nonlinear Dynamics. https://doi.org/10.1007/s11071-010-9683-9

Brooks-Pollock, E., Roberts, G. O., & Keeling, M. J. (2014). A dynamic model of bovine tuberculosis spread and control in Great Britain. Nature. https://doi.org/10.1038/nature13529

Byrne, A. L., Marais, B. J., Mitnick, C. D., Lecca, L., & Marks, G. B. (2015). Tuberculosis and chronic respiratory disease: A systematic review. In International Journal of Infectious Diseases. https://doi.org/10.1016/j.ijid.2014.12.016

Campos, C., Silva, C. J., & Torres, D. F. M. (2020). Numerical optimal control of HIV transmission in OCTAVe/MATLAB. Mathematical and Computational Applications. https://doi.org/10.3390/mca25010001

Chambers, M. L., Pontryagin, L. S., Boltyanskii, V. G., Gamkrelidze, R. V., Mishchenko, E. F., & Brown, D. E. (1965). The Mathematical Theory of Optimal Processes. OR. https://doi.org/10.2307/3006724

Choi, S., Jung, E., & Lee, S. M. (2015). Optimal intervention strategy for prevention tuberculosis using a smoking-tuberculosis model. Journal of Theoretical Biology. https://doi.org/10.1016/j.jtbi.2015.05.022

Emvudu, Y., Demasse, R., & Djeudeu, D. (2011). Optimal control of the lost to follow up in a tuberculosis model. Computational and Mathematical Methods in Medicine. https://doi.org/10.1155/2011/398476

Fatmawati, Dyah Purwati, U., Riyudha, F., & Tasman, H. (2020). Optimal control of a discrete age-structured model for tuberculosis transmission. Heliyon. https://doi.org/10.1016/j.heliyon.2019.e03030

Gao, D. peng, & Huang, N. jing. (2018). Optimal control analysis of a tuberculosis model. Applied Mathematical Modelling. https://doi.org/10.1016/j.apm.2017.12.027

Kaufman, H. (1964). The Mathematical Theory of Optimal Processes, by L. S. Pontryagin, V. G. Boltyanskii, R. V. Gamkrelidze, and E. F. Mishchenko. Authorized Translation from the Russian. Translator: K. N. Trirogoff, Editor: L.. W. Neustadt. Interscience Publishers (division. Canadian Mathematical Bulletin. https://doi.org/10.1017/s0008439500032112

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. https://doi.org/10.1016/j.jtbi.2018.01.026

Kuddus, M. A., Meeha, M. T., Whit, L. J., McBryd, E. S., & Adekunl, A. I. (2020). Modeling drug-resistant tuberculosis amplification rates and intervention strategies in Bangladesh. PLoS ONE. https://doi.org/10.1371/journal.pone.0236112

Kyu, H. H., Maddison, E. R., Henry, N. J., Ledesma, J. R., Wiens, K. E., Reiner, R., Biehl, M. H., Shields, C., Osgood-Zimmerman, A., Ross, J. M., Carter, A., Frank, T. D., Wang, H., Srinivasan, V., Abebe, Z., Agarwal, S. K., Alahdab, F., Alene, K. A., Ali, B. A., … Murray, C. J. L. (2018). Global, regional, and national burden of tuberculosis, 1990-2016: Results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 Study. The Lancet Infectious Diseases. https://doi.org/10.1016/S1473-3099(18)30625-X

Moualeu, D. P., Weiser, M., Ehrig, R., & Deuflhard, P. (2015). Optimal control for a tuberculosis model with undetected cases in Cameroon. Communications in Nonlinear Science and Numerical Simulation. https://doi.org/10.1016/j.cnsns.2014.06.037

Seierstad, A., & Sydsaeter, K. (1977). Sufficient Conditions in Optimal Control Theory. International Economic Review. https://doi.org/10.2307/2525753

Zhang, W. (2020). Analysis of an in-host tuberculosis model for disease control. Applied Mathematics Letters. https://doi.org/10.1016/j.aml.2019.07.014

Zhang, W., Frascoli, F., & Heffernan, J. (2020). Analysis of solutions and disease progressions for a within-host Tuberculosis model. Mathematics in Applied Sciences and Engineering. https://doi.org/10.5206/mase/10221




DOI: https://doi.org/10.31764/jtam.v5i1.3813

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