References
[1] Torres, DFM, Ndaïrou, F, Area, I, Nieto, JJ. Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan. Chaos, Solitons and Fractals, http://ees.elsevier.com; 2020 [accessed 02, September, 2020].
[2] Gumel, AB. (2020). Using mathematics to understand and control the coronavirus pandemic, https://opinion.premiumtimesng. com/2020/05/04/using-mathematics tounderstand-and-control-the-coronavirus-pandemic-by-abba-b-gumel/; 2020 [accessed 16, August, 2020].
[3] Nita, HS, Ankush, HS, Ekta, NJ. (2020). Control strategies to curtail transmission of COCID-19. Intl. J. Maths. and Mathcal. Sc., 2020; 1-12. http://downloads.hindawi.com/journals/ijmms/2020/2649514.pdf.
[4] World Health Organization. (2020). COVID-19 Weekly Epidemiological Update, https://www.who.int/publications/m/item/ weekly-epidemiological-update---27-october-2020; 2020 [accessed 27, October, 2020].
[5] Nigeria Centre for Disease Control. (2020). Coronavirus disease (COVID-19) pandemic, https://ncdc.gov.ng/#; 2020 [accessed 27, October, 2020].
[6] Grigorieva, E, Khailov, E, Korobeinikov, A. (2020). Optimal quarantine strategies for COVID-19 control models. https://arxiv.org/pdf/ 2004.10614.pdf; 2020 [accessed 29, August, 2020].
[7] Leslie, M. (2020). T cells found in coronavirus patients 'bode well' for long-term immunity, http://science.sciencemag.org/ content/368/6493/809; 2020 [accessed 14, August, 2020].
[8] Bassey, E. B., Atsu, U. J. (2021). Global stability analysis of the role of multi-therapies and non-pharmaceutical treatment protocols for COVID-19 pandemic. Chaos, Solitons and Fractals, 143(2021), 110574. https://pubmed.ncbi.nlm.nih.gov/33519116/.
[9] Jahanshahi, H., Yousefpour, A., Bekires, S. (2020). Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak. Chaos, Solitons and Fractals, 2020; 136: 1-6. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229919/.
[10] Wu, JT, Leung, K, Leung, GM. (2020). Nowcasting and forecasting the potential domestic and international spread of the 2019.nCoV outbreak originating in Wuhan, China: a modeling study. The Lacet 2020; 395(10225):689-697. https://www.thelancet.com/action/showPdf?pii=S0140-6736%2820%2930260-9.
[11] Peng, L, Yang, W, Zhang, D, Zhuge, C, Hong, L. (2020). Epidemic analysis of COVID-19 in China by dynamical modeling, http://arxiv.org/abs/2002.06563; 2020 [accessed 14, August, 2020].
[12] Obsu, LL, Balcha, FS. (2020). Optimal control strategies for the transmission risk of COVID-19. Journal of Biological Dynamics 2020; 14(1): 590-607. https://www.tandfonline.com/doi/full/10.1080/17513758.2020.1788182.
[13] Moore, SE, Okyere, E. (2020). Controlling the transmission dynamics of COVID-19. ArXiv. 2020; 2004.00443, https://arxiv.org/pdf/2004.00443.pdf; 2020 [accessed 10 August, 2020].
[14] Sasmita, NR, Ikhwan, M, Suyanto, S, Chongsuvivatwong, V. (2020). Optimal control on a mathematical model to pattern the progression of coronavirus disease 2019 (COVID-19) in Indonesia. Global Health Research and Policy 2020; 5(38): 1-12. https://ghrp.biomedcentral.com/articles/10.1186/s41256-020-00163-2.
[15] Lee, D, Nasud, MA, Kim, BN, Oh, C. (2017). Optimal control analysis for the MEERS-CoV outbreak: South Korea perspectives. J. Korea Soc. Indust. Appl. Math 2017; 21(3): 143-154. http://koreascience.or.kr/article/JAKO201728441290805.pdf.
[16] Imai, N, Cori, A, Dorigatti, I, et al. (2020). MRC Centre for Global Infectious Disease Analysis: Wuhan coronavirus reports 1-3, https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-transmissibility-25-01-2020.pdf; 2020 [accessed 21 November, 2020].
[17] Wahid, BKA, Moustapha, D, Rabi, HG, Bisso, S. (2020). Contribution to the Mathematical Modeling of COVID-19 in Niger. Applied Mathematics 2020; 11: 427-435. https://doi.org/10.4236/am.2020.116030.
[18] AL-Husseiny, HF, Mohsen, AA, Zhou, X. (2020). A dynamical behavior of COVID-19 virus model with carrier effect to Out-break Epidemic. Research Square//Preprint, https://www.researchsquare.com/article/rs-24219/v1; 2020 [accessed 12, August, 2020].
[19] Danane, J, Allali, K. (2018). Mathematical Analysis and Treatment for a Delayed Hepatitis B Viral Infection Model with the Adaptive Immune Response and DNA-Containing Capsids. High-Throughput 2018; 7(35): 1-16. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6306857/.
[20] Fister, KR, Lenhart, S, McNally, JS. (1998). Optimizing chemotherapy in an HIV Model. Electr. J. Diff. Eq. 1998; 32: 1-12. http://emis.matem.unam.mx/journals/EJDE/1998/32/fister.pdf
[21] Hattaf, K, Yousfi, N. (2012). Optimal control of a delayed HIV infection model with immune response using an efficient numerical method. Biomathematics 2012; 1-7.
[22] Joshi, HR. (2002). Optimal Control of an HIV Immunology Model. Optimal Control Applications and Methods 2002; 23:199-213. http://www.math.utk.edu/~lenhart/docs/hiv.pdf.
[23] Kahuru, J, Luboobi, L, Nkansah-Gyekye, Y. (2017). Optimal control techniques on a mathematical model for the dynamics of tungiasis in a community. Intl. J. Maths and Mathcal. Sc. 2017; 1-9. https://www.hindawi.com/journals/ijmms/2017/4804897/.
[24] Bassey, EB. (2021). Optimal multi-therapeutic protocols for the control of cholera mortality rate. 39th Annual Conference of the Nigeria Mathematical Society (NMS-RUN 2020), C40:(46). Retrieved date: [12, April, 2021], online available at https://www.app.nigerianmathematicalsociety.org/conference.
[25] Fleming, W, Rishel, R. (1975). Deterministic and Stochastic Optimal Control. Springer Verlag: New York; 1975. http://dx.doi.org/10.1007/978-1-4612- 6380-7.
[26] Culshaw, R, Ruan, S, Spiteri, RJ. (2004). Optimal HIV Treatment by Maximizing Immune Response. Journal of Mathematical Biology 2004; 48(5): 545-562. https://miami.pure.elsevier.com/en/publications/optimal-hiv-treatment-by-maximising-immun e-response.
[27] Bassey, BE. (2020). Optimal control dynamics: Multi-therapies with dual immune response for treatment of dual delayed HIV-HBV Infections. I.J. Mathematical Sciences and Computing 2020c; 6(2):18-60. http://www.mecs-press.org/ijmsc/ijmsc -v6-n2/IJMSC-V6-N2-2.pdf
[28] Pontryagin, LS, Boltyanskii, VG, Gamkrelize, RV, Mishchenko, EF. (1967). The Mathematical Theory of Optimal Processes. Wiley: New York; 1967. https://onlinelibrary.wiley.com/doi/abs/10.1002/zamm.19630431023.