MATHEMATICAL ASSESSMENT AND STABILITY ANALYSIS OF HIV/AIDS EPIDEMIC MODEL WITH VERTICAL TRANSMISSION AND TREATMENT
Main Article Content
Okunloye Ayinde Adepoju
Hammed Ibrahim*
Wasiu Omotayo Salahu
This study presents a mathematical assessment of the dynamics of HIV/AIDS epidemic with vertical transmission and treatment. The well-posedness is analyzed using the theories of positivity and boundedness. Using the next generation matrix approach, the model’s basic reproduction number was obtained. The findings from the analysis also revealed that the model possesses two equilibrium points, the locally stable HIV/AIDS free equilibrium when the threshold parameter is less than unity and endemic equilibrium when R0 > 1. The impact of the parameters associated to the basic reproduction number R0 is investigated using the normalized forward sensitivity index. Furthermore, the model is expanded to incorporate time-dependent antiretroviral treatment and the use of condom. The model’s qualitative analysis is supported by numerical simulation.
Adepoju, O. A., & Ibrahim, H. O. (2024). An optimal control model for monkeypox transmission dynamics with vaccination and immunity loss following recovery. Healthcare Analytics, 6, 100355.
Adepoju, O. A., & Olaniyi, S. (2021). Stability and optimal control of a disease model with vertical transmission and saturated incidence. Scientific African, 12, e00800.
Agusto, F. B., & Gumel, A. B. (2010). Theoretical assessment of avian influenza vaccine. DCDS Series B, 13(1), 1–25.
Akinwumi, T. O., Olopade, I. A., Adesanya, A. O., & Alabi, M. O. (2021). A mathematical model for the transmission of HIV/AIDS with early treatment.
Ayele, T. K., Goufo, E. F. D., & Mugisha, S. (2021). Mathematical modeling of HIV/AIDS with optimal control: a case study in Ethiopia. Results in Physics, 26, 104263.
Baryarama, F., Mugisha, J. Y. T., & Luboobi, L. S. (2006). Mathematical model for HIV/AIDS with complacency in a population with declining prevalence. Computational and Mathematical Methods in Medicine, 7(1), 27–35.
Bolaji, B., Onoja, T., Agbata, C., Omede, B. I., & Odionyenma, U. B. (2024). Dynamical analysis of HIV-TB co-infection transmission model in the presence of treatment for TB. Bulletin of Biomathematics, 2(1), 21–56.
Cai, L., Li, X., Ghosh, M., & Guo, B. (2009). Stability analysis of an HIV/AIDS epidemic model with treatment. Journal of Computational and Applied Mathematics, 229(1), 313–323.
CDC, Center for Diseases Control and Prevention (2023). Information on HIV/AIDS. https://www.cdc.gov/hiv/about/index.html
Cheneke, K. R., Rao, K. P., & Edessa, G. K. (2021). Bifurcation and stabillity analysis of HIV transmission model with optimal control. Journal of Mathematics, 2021(1), 7471290.
Chitnis, N., Smith, T., & Steketee, R. (2008). A mathematical model for the dynamics of malaria in mosquitoes feeding on a heterogeneous host population. Journal of Biological Dynamics, 2(3), 259–285.
Diekmann, O., Heesterbeek, J. A. P., & Metz, J. A. J. (1990). On the definition and the computation of the basic reproduction ratio R 0 in models for infectious diseases in heterogeneous populations. Journal of Mathematical Biology, 28, 365–382.
Egonmwan, A. O., & Okuonghae, D. (2019). Analysis of a mathematical model for tuberculosis with diagnosis. Journal of Applied Mathematics and Computing, 59, 129–162.
Erinle-Ibrahim, L. M., Adebimpe, O., Lawal, W. O., & Agbomola, J. O. (2022). A mathematical model and sensitivity analysis of Lassa fever with relapse and reinfection rate. Tanzania Journal of Science, 48(2), 414–426.
Espitia, C. C., Botina, M. A., Solarte, M. A., Hernandez, I., Riascos, R. A., & Meyer, J. F. (2022). Mathematical model of HIV/AIDS considering sexual preferences under antiretroviral therapy, a case study in san juan de pasto, colombia. Journal of Computational Biology, 29(5), 483–493.
Glass, T., Myer, L., & Lesosky, M. (2020). The role of HIV viral load in mathematical models of HIV transmission and treatment: a review. BMJ Global Health, 5(1), e001800.
Gurmu, E. D., Bole, B. K., & Koya, P. R. (2020). Mathematical modelling of HIV/AIDS transmission dynamics with drug resistance compartment. American Journal of Applied Mathematics, 8(1), 34–45.
Ibrahim, I. A., Daniel, E. E., Danhausa, A. A., Adamu, M. U., Shawalu, C. J., & Yusuf, A. (2021). Mathematical Modelling of Dynamics of HIV Transmission Depicting the Importance of Counseling and Treatment. Journal of Applied Sciences and Environmental Management, 25(6), 893–903.
Kaymakamzade, B., Şanlıdağ, T., Hınçal, E., Sayan, M., Sa’ad, F. T., & Baba, I. A. (2018). Role of awareness in controlling HIV/AIDS: a mathematical model. Quality & Quantity, 52, 625–637.
Kimbir, R. A., Udoo, M. J. I., & Aboiyar, T. (2012). A mathematical model for the transmission dynamics of HIV/AIDS in a two-sex population Counseling and Antiretroviral Therapy (ART). J. Math. Comput. Sci., 2(6), 1671–1684.
Lenhart, S., & Workman, J. T. (2007). Optimal control applied to biological models. Chapman and Hall/CRC.
Naresh, R., Tripathi, A., & Omar, S. (2006). Modelling the spread of AIDS epidemic with vertical transmission. Applied Mathematics and Computation, 178(2), 262–272.
Olaniyi, S., Ajala, O. A., & Abimbade, S. F. (2023). Optimal control analysis of a mathematical model for recurrent malaria dynamics. Operations Research Forum, 4(1), 14.
Olaniyi, S., & Chuma, F. M. (2023). Lyapunov stability and economic analysis of monkeypox dynamics with vertical transmission and vaccination. International Journal of Applied and Computational Mathematics, 9(5), 85.
Olaniyi, S., Kareem, G. G., Abimbade, S. F., Chuma, F. M., & Sangoniyi, S. O. (2024). Mathematical modelling and analysis of autonomous HIV/AIDS dynamics with vertical transmission and nonlinear treatment. Iranian Journal of Science, 48(1), 181–192.
Olaniyi, S., Okosun, K. O., Adesanya, S. O., & Areo, E. A. (2018). Global stability and optimal control analysis of malaria dynamics in the presence of human travelers. The Open Infectious Diseases Journal, 10(1).
Olaniyi, S., Okosun, K. O., Adesanya, S. O., & Lebelo, R. S. (2020). Modelling malaria dynamics with partial immunity and protected travellers: optimal control and cost-effectiveness analysis. Journal of Biological Dynamics, 14(1), 90–115.
Omale, D., & Aja, R. O. (2019). Stability Analysis of the Mathematical Model on the Control of HIV/AIDS Pandemic in a Heterogeneous Population. Earthline Journal of Mathematical Sciences, 2(2), 433–460.
Omondi, E. O., Mbogo, R. W., & Luboobi, L. S. (2018). Mathematical modelling of the impact of testing, treatment and control of HIV transmission in Kenya. Cogent Mathematics & Statistics, 5(1), 1475590.
Oyovwevotu, S. O. (2021). Mathematical modelling for assessing the impact of intervention strategies on HIV/AIDS high risk group population dynamics. Heliyon, 7(10).
Pontryagin, L. S. (2018). Mathematical theory of optimal processes. Routledge.
Rois, M. A., Trisilowati, T., & Habibah, U. (2021). Local sensitivity analysis of COVID-19 epidemic with quarantine and isolation using normalized index. Telematika, 14(1), 13–24.
Safiel, R., Massawe, E. S., & Makinde, O. D. (2012). Modelling the Effect of Screening and Treatment on Transmission of HIV/AIDS Infection in a Population. American Journal of Mathematics and Statistics, 2(4), 75–88.
Tasman, H., Aldila, D., Dumbela, P. A., Ndii, M. Z., Fatmawati, Herdicho, F. F., & Chukwu, C. W. (2022). Assessing the impact of relapse, reinfection and recrudescence on malaria eradication policy: a bifurcation and optimal control analysis. Tropical Medicine and Infectious Disease, 7(10), 263.
Twagirumukiza, G., & Singirankabo, E. (2021). Mathematical analysis of a delayed HIV/AIDS model with treatment and vertical transmission. Open Journal of Mathematical Sciences, 5(1), 128–146.
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), 29–48.
WHO, World Health Organization. (2023). HIV/AIDS fact sheet. https://www.who.int/news-room/fact-sheets/detail/hiv-aids
Yusuf, T. T., & Benyah, F. (2012). Optimal strategy for controlling the spread of HIV/AIDS disease: a case study of South Africa. Journal of Biological Dynamics, 6(2), 475–494.
Okunloye Ayinde Adepoju , Department of Pure and Applied Mathematics, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
Senior Lecturer