[1] Ali Biswas, H. On the evolution of AIDS/HIV treatment: an optimal control approach, Curr. HIV Res. 12(1), (2014), 1–12.
[2] Akudibillah G., Pandey A., and Medlock J. Optimal control for HIV treatment. Math. Biosci. Eng. 16(1), (2018), 373–396.
[3] Arenas, A.J., González-Parra, G., Naranjo, J.J., Cogollo, M. and De La Espriella, N. Mathematical analysis and numerical solution of a model of HIV with a discrete time delay, Mathematics, 9(3), (2021), 257.
[4] Bakare, E.A. and oskova-Mayerova S.Optimal control analysis of cholera dynamics in the presence of asymptotic transmission, Axioms 10 (2), (2021), 60.
[5] Bórquez, A., Guanira, J.V., Revill, P., Caballero, P., Silva-Santisteban, A., Kelly, S., Salazar, X., Bracamonte, P., Minaya, P., Hallett, T.B. and Cáceres, C.F. The impact and cost-effectiveness of combined HIV prevention scenarios among transgender women sex-workers in Lima, Peru: a mathematical modelling study, The Lancet Public Health, 4(3), (2019), e127–e136.
[6] Boukhouima, A., Lotfi, E.M., Mahrouf, M., Rosa, S., Torres, D.F. and Yousfi, N. Stability analysis and optimal control of a fractional HIV-AIDS epidemic model with memory and general incidence rate, Eur. Phys. J. Plus, 136(1), (2021), 1–20.
[7] Camlin, C.S., Koss, C.A., Getahun, M., Owino, L., Itiakorit, H., Akatuk-wasa, C., Maeri, I., Bakanoma, R., Onyango, A., Atwine, F. and Ayieko, J. Understanding demand for PrEP and early experiences of PrEP use among young adults in rural Kenya and Uganda: a qualitative study, AIDS Behav. 24, (2020), 2149–2162.
[8] Campos, C., Silva, C.J. and Torres, D.F. Numerical optimal control of HIV transmission in Octave/MATLAB, Math. Comput. Appl. 25(1) (2020), Paper No. 1, 20 pp.
[9] Campos, N.G., Lince-Deroche, N., Chibwesha, C.J., Firnhaber, C., Smith, J.S., Michelow, P., Meyer-Rath, G., Jamieson, L., Jordaan, S., Sharma, M. and Regan, C. Cost-effectiveness of cervical cancer screen-ing in women living with HIV in South Africa: a mathematical modeling study. Acquir. Immune Defic. Syndr. (1999), 79(2) (2018), 195.
[10] Cheneke, K.R. Optimal Control and Bifurcation Analysis of HIV Model, Comput. Math. Methods Med. (2023).
[11] Cheneke, K.R., Rao, K.P. and Edessa, G.K. Application of a new gen-eralized fractional derivative and rank of control measures on cholera transmission dynamics, International Journal of Mathematics and Math-ematical Sciences, 2021, (2021), 1–9.
[12] Cheneke, K.R., Rao, K.P. and Edessa, G.K. Bifurcation and stabillity analysis of HIV transmission model with optimal control, J. Math. 2021, (2021), 1–14.
[13] Choi, H., Suh, J., Lee, W., Kim, J.H., Kim, J.H., Seong, H., Ahn, J.Y., Jeong, S.J., Ku, N.S., Park, Y.S. and Yeom, J.S. Cost-effectiveness analysis of pre-exposure prophylaxis for the prevention of HIV in men who have sex with men in South Korea: a mathematical modelling study, Sci. Rep. 10(1), (2020), 14609.
[14] Ðorđević, J. and Rognlien Dahl, K., 2022. Stochastic optimal control of pre-exposure prophylaxis for HIV infection, Math, Med. Biol. 39(3), (2022), 197–225.
[15] Ghosh, I., Tiwari, P.K., Samanta, S., Elmojtaba, I.M., Al-Salti, N. and Chattopadhyay, J. A simple SI-type model for HIV/AIDS with media and self-imposed psychological fear, Math. Biosci. 306 (2018), 160–169.
[16] Hattaf, K. and Yousfi, N. Two optimal treatments of HIV infection model, World J. Model. Simul. 8(1), (2012), 27–36.
[17] Hattaf, K. and Yousfi, N. Optimal control of a delayed HIV infection model with immune response using an efficient numerical method, Int. Sch. Res. Notices, (2012).
[18] Hidayat, N., R. B. E. Wibowo, et al., Marsudi, Hidayat, N. and Wibowo, R. B. E. Optimal control and cost-effectiveness analysis of HIV model with educational campaigns and therapy, Matematika (Johor) 35 (2019), Special issue, 123–138.
[19] Hove-Musekwa, S.D., Nyabadza, F., Mambili-Mamboundou, H., Chiyaka, C. and Mukandavire, Z. Cost-effectiveness analysis of hospital-ization and home-based care strategies for people living with HIV/AIDS: the case of Zimbabwe, Int. Sch. Res. Notices, (2014).
[20] Huo, H.-F., Chen, R. and Wang, X.-Y. Modelling and stability of HIV/AIDS epidemic model with treatment, Appl. Math. Model. 40(13-14) (2016), 6550–6559.
[21] Huo, H.-F. and Li-Xiang, F. Global stability for an HIV/AIDS epidemic model with different latent stages and treatment. Applied Mathematical Modelling, 37(3) (2013), 1480–1489.
[22] Khajanchi, S., Bera, S. and Roy, T.K. Mathematical analysis of the global dynamics of a HTLV-I infection model, considering the role of cytotoxic T-lymphocytes, Math. Comput. Simul. 180 (2021), 354–378.
[23] Marsudi, M., Hidayat, N. and Wibowo, R.B.E. Application of Optimal Control Strategies for the Spread of HIV in a Population, J. Life Sci. Res. 4(1) (2017), 1–9.
[24] Marsudi, T., Suryanto, A. and Darti, I. Global stability and optimal control of an HIV/AIDS epidemic model with behavioral change and treatment. Eng. Lett. 29(2) (2021).
[25] Naik, P.A., Yavuz, M., Qureshi, S., Zu, J. and Townley, S. Modeling and analysis of COVID-19 epidemics with treatment in fractional derivatives using real data from Pakistan, Eur. Phys. J. Plus, 135 (2020), 1–42.
[26] Olaniyi, S., Obabiyi, O.S., Okosun, K.O., Oladipo, A.T. and Ade-wale, S.O. Mathematical modelling and optimal cost-effective control of COVID-19 transmission dynamics, Eur. Phys. J. Plus, 135(11) (2020), 938.
[27] Silva, C.J. and Torres, D.F. Modeling and optimal control of HIV/AIDS prevention through PrEP. arXiv preprint arXiv:1703.06446 (2017).