Mathematical modelling and vaccination acceptability analysis of COVID-19 in Nigeria

Document Type : Original Article


1 Department of mathematics, University of Ilorin, Nigeria

2 Department of Mathematics, University of Ilorin, Nigeria

3 Department of Mathematics, Nigerian Army University Biu, Nigeria


Abstract: The novel coronavirus 2019 known as (COVID-19) pandemic caused by SARS-CoV-2 occurred in Wuhan town of China in 2019. The virus has rapidly spread all over the world and has continued to affect the public well-being. This paper focuses on a mathematical model with vaccination acceptability of COVID-19 with which to examine to what extent the vaccine would be accepted in Nigeria. Specifically, the paper introduces a compartmental model to measure the potential impact of the COVID-19 vaccine. The vaccination acceptability model results show that up to 80% of the Nigerian populace accepted the vaccination campaign, despite the gabs on the COVID-19 vaccine by some health workers and the communities in Nigeria. It also shows that 90% vaccinated susceptible plus 50% effectiveness of face-mask use has brought about a decrease of the pandemic while mortality rate has decreased drastically which shows that the vaccine is effective. The result also reveals that the recovered individuals from COVID-19 have increased in alignment and, the vaccine has a significant impact on the populace. Finally, possible extensions of the model as well as open challenges associated with the formulation and analysis of COVID-19 dynamics will be addressed.


[1] A. Bernoussi and K. Hattaf, Global Dynamics of an SIRSI Epidemic Model with Discrete Delay and General
Incidence Rate, Journal of Applied Nonlinear Dynamics, 10(3) 2021, 547-562.
[2] H. Branswell and A. Joseph, WHO declares the coronavirus outbreak –a pandemic. Stat, 2020.
[3] Z. Cakir and H. B. Savaş, A mathematical modelling for the COVID-19 pandemic in Iran, Ortadoğu Tıp Dergisi,
12(2) 2020, 206-210.
[4] A.P. Chiedozie, O.J. Chukwuebuka, C.F. Chidimma, O.V. Onyinyechi, A.K. Chijioke, O.S. Chibuzor and U.B.
Chioma, Willingness to Accept a Potential COVID-19 Vaccine in Nigeria, American Journal of Medical Sciences,
9(1) 2021, 1-5.
[5] D. Dejene, T. Worku and P.R. Koya, Modelling the Transmission and Dynamics of COVID-19 Using Self-protection and Isolation as Control Measures. Mathematical Modelling and Applications, 5(3) 2020, 191.
[6] A.B. Gumel, E.A. Iboi, C.N. Ngonghala, E.H. Elbasha, A primer on using mathematics to understand COVID-19 dynamics: Modeling, analysis and simulations. Infectious Disease Modelling, (6) 2021, 148-168.
[7] C. Huang, Y. Wang, X. Li, L. Ren, J. ZhaoY. Hu and B.Cao, Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China, The lancet, 395(10223) 2020, 497-506.
[8] E.A. Iboi, O.O. Sharomi, C.N. Ngonghala, A.B. Gumel, Mathematical Modeling and Analysis of COVID-19 pandemic in Nigeria, medRxiv, 2020.
[9] E.A. Iboi, C.N. Ngonghala, A.B. Gumel, Will an imperfect vaccine curtail the COVID-19 pandemic in the US?, Infectious Disease Modelling, (5) 2020, 510-524.
[10] A. Kouidere, B. Khajji, A. El-Bhih, O. Balatif, R. Rachik, Mathematical modelling with optimal control strategy of transmission of COVID-19 pandemic virus. Commun. Math. Biol. Neurosci, 2020.
[11] O.A. MacLean, S. Lytras, S. Weaver, J.B. Singer, M.F. Boni, P. Lemey, D.L. Robertson, Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen, PLoS Biology, 19(3) 2021, e3001115.
[12] M. Martcheva, An introduction to mathematical epidemiology 61 2015, New York: Springer.
[13] A. McDonnell, R. Van Exan, S. Lloyd, L. Subramanian, K. Chalkidou, A. La Porta, D. Reader, COVID-19 Vaccine predictions: using mathematical modelling and expert opinions to estimate timelines and probabilities of success of COVID-19 vaccines, Center for Global Development Washington, 2020.
[14] D.R. Merkin, Introduction to the Theory of Stability 24 2012, Springer Science & Business Media.
[15] National Primary Health Care Development Agency, COVID-19 vaccinated update 2021, Retrieved from (accessed 5th July 2021).
[16] Nigerian Centre for Disease Control, 2021, Retrieved from (accessed 1st of July 2021).
[17] C.N. Ngonghala, E. Iboi, S. Eikenberry, M. Scotch, C.R. MacIntyre, M.H. Bonds, A.B. Gumel, Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus. Mathematical biosciences, (325) 2020, 108364.
[18] D. Okuonghae and A. Omame, Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria. Chaos, Solitons & Fractals, (139) 2020, 110032.
[19] S.M. Sherman, L.E. Smith, J. Sim, R. Amlôt, M. Cutts, H. Dasch, N. Sevdalis, COVID-19 vaccination intention in the UK: results from the COVID-19 vaccination acceptability study (CoVAccS), a nationally representative cross-sectional survey. Human vaccines & immunotherapeutics, 17(6) 2021, 1612-1621.
[20] P. Van den Driessche, Reproduction numbers of infectious disease models. Infectious Disease Modelling, 2(3) 2017, 288-303.
[21] P. Van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical biosciences, 180(1-2) 2002, 29-48.
[22] World Health Organization, COVID-19 weekly epidemiological update, 2020.
[23] World Health Organization, Interim recommendations for use of the Pfizer–BioNTech COVID-19 vaccine, BNT162b2, under emergency use listing: interim guidance, first issued 8 January 2021, updated 15 June 2021 (No. WHO/2019-nCoV/vaccines/SAGE_recommendation//BNT162b2/2021.2), 2021, World Health Organization.
[24] World Health Organization, Mission summary: WHO Field Visit to Wuhan, China 20-21 January 2020. Online information available at https://www. who. int/china/news/detail/22-01-2020-field-visit-wuhan-china-jan-2020 (accessed 19th April 2020).
[25] World Health Organization, Overview of public health and social measures in the context of COVID-19: interim guidance, 18 May 2020 (No. WHO/2019-nCoV/PHSM_Overview 2020, World Health Organization.
[26] Z.Q. Xia, J. Zhang Y.K. Xue, G.Q. Sun, Z. Jin, Modeling the transmission of Middle East respirator syndrome Corona virus in the Republic of Korea. PloS one, 10(12) 2015, 0144778.
[27] N. Zhu, D. Zhang, W. Wang, X. Li, B. Yang, J. Song, W. Tan, A novel Coronavirus from patients with pneumonia in China, New England journal of medicine, 2020.
[28] H.A. Lyeme, Mathematical modeling of the impacts of the nanoparticle in River-Aquatic system with convective cooling, Mathematics and Computational Sciences, 1(4) 2021, 1-3.
Volume 2, Issue 4
December 2021
Pages 24-40
  • Receive Date: 28 September 2021
  • Revise Date: 02 November 2021
  • Accept Date: 03 November 2021
  • First Publish Date: 03 November 2021