Abstract
In this work, we examine the impact of certain preventive measures for effective measles control. To do this, a mathematical model for the dynamics of measles transmission is developed and analyzed. A suitable Lyapunov function is used to establish the global stability of the equilibrium points. Our analysis shows that the disease-free equilibrium is globally stable, with the measles dying out on the long run because the reproduction number \({\mathcal {R}}_{0}\le 1\). The condition for the global stability of the endemic equilibrium is also derived and analyzed. Our findings show that when \({\mathcal {R}}_0> 1\), the endemic equilibrium is globally stable in the required feasible region. In this situation, measles will spread across the populace. A numerical simulation was performed to demonstrate and support the theoretical findings. The results suggest that lowering the effective contact with an infected person and increasing the rate of vaccinating susceptible people with high-efficacy vaccines will lower the prevalence of measles in the population.
Similar content being viewed by others
Data Availability
Data used to support the findings of this study are included in the article. The authors used a set of parameter values whose sources are from the literature as shown in Table 1.
References
World Health Organization (2018) Measles. http://www.who.int/news-room/fact-sheets/detail/measles
Aldila D, Asrianti D (2019) A deterministic model of measles with imperfect vaccination and quarantine intervention. In: Journal of physics: conference series, vol 1218. IOP Publishing, p 012044
Dales L, Kizer KW, Rutherford G, Pertowski C, Waterman S, Woodford G (1993) Measles epidemic from failure to immunize. West J Med 159(4):455
World Health Organization (2019) Measles. https://www.who.int/news/item/15-05-2019-new-measles-surveillance-data-for-2019
Kuddus MA, Mohiuddin M, Rahman A (2021) Mathematical analysis of a measles transmission dynamics model in Bangladesh with double dose vaccination. Sci Rep 11(1):1–16
Nigeria Centre for Disease Control (2019) Measles. https://ncdc.gov.ng/diseases/info/m
Tilahun GT, Demie S, Eyob A (2020) Stochastic model of measles transmission dynamics with double dose vaccination. Infect Dis Model 5:478–494
Centre for Disease Control and Prevention (2019) Measles. https://www.cdc.gov/measles/symptoms/complications.html
Markowitz LE, Tomasi A, Sirotkin BI, Carr RW, Davis RM, Preblud SR, Orenstein WA (1987) Measles hospitalizations, united states, 1977–84: comparison with national surveillance data. Am J Public Health 77(7):866–868
Lee B, Ying M, Stevenson J, Seward JF, Hutchins SS (2004) Measles hospitalizations, United States, 1985–2002. J Infect Dis 189(1Supplement–):S210–S215
Peter OJ, Viriyapong R, Oguntolu FA, Yosyingyong P, Edogbanya HO, Ajisope MO (2020) Stability and optimal control analysis of an SCIR epidemic model. J Math Comput Sci 10(6):2722–2753
Peter OJ, Kumar S, Kumari N, Oguntolu FA, Oshinubi K, Musa R (2022) Transmission dynamics of Monkeypox virus: a mathematical modelling approach. Model Earth Syst Environ. 8:3423–3434. https://doi.org/10.1007/s40808-021-01313-2
Peter OJ, Qureshi S, Yusuf A, Al-Shomrani M, Idowu AA (2021) A new mathematical model of Covid-19 using real data from Pakistan. Results Phys 24:104098
Peter OJ, Yusuf A, Oshinubi K, Oguntolu FA, Lawal JO, Abioye AI, Ayoola TA (2021) Fractional order of pneumococcal pneumonia infection model with Caputo Fabrizio operator. Results Phys 29:104581
Peter OJ (2020) Transmission dynamics of fractional order brucellosis model using caputo-fabrizio operator. Int J Differ Equ. https://doi.org/10.1155/2020/2791380
Abioye A, Ibrahim M, Peter O, Amadiegwu S, Oguntolu F (2018) Differential transform method for solving mathematical model of SEIR and SEI spread of malaria. Int J Sci Basic Appl Res 40(1):197–219
Abioye AI, Peter OJ, Ogunseye HA, Oguntolu FA, Oshinubi K, Ibrahim AA, Khan I (2021) Mathematical model of Covid-19 in Nigeria with optimal control. Results Phys 28:104598
Ayoola TA, Edogbanya HO, Peter OJ, Oguntolu FA, Oshinubi K, Olaosebikan ML (2021) Modelling and optimal control analysis of typhoid fever. J Math Comput Sci 11(6):6666–6682
Peter O, Ibrahim M, Oguntolu F, Akinduko O, Akinyemi S (2018) Direct and indirect transmission dynamics of typhoid fever model by differential transform method. J Sci Technol Educ 6:167–177
Bakare E, Adekunle Y, Kadiri K (2012) Modelling and simulation of the dynamics of the transmission of measles. Int J Comput Trends Technol 3:174–178
Okyere-Siabouh S, Adetunde I (2013) Mathematical model for the study of measles in cape coast metropolis. Int J Mod Biol Med 4(2):110–133
Tessa OM (2006) Mathematical model for control of measles by vaccination. Proc Mali Symp Appl Sci 2006:31–36
Huang J, Ruan S, Wu X, Zhou X (2018) Seasonal transmission dynamics of measles in China. Theory Biosci 137(2):185–195
Momoh A, Ibrahim M, Uwanta I, Manga S (2013) Mathematical model for control of measles epidemiology. Int J Pure Appl Math 87(5):707–717
Musyoki E, Ndungu R, Osman S (2019) A mathematical model for the transmission of measles with passive immunity. Int J Res Math Stat Sci 6(2):1–8
Ogunmiloro OM, Idowu AS, Ogunlade TO, Akindutire RO (2021) On the mathematical modeling of measles disease dynamics with encephalitis and relapse under the Atangana–Baleanu–Caputo fractional operator and real measles data of Nigeria. Int J Appl Comput Math 7(5):1–20
Peter O, Afolabi O, Victor A, Akpan C, Oguntolu F (2018) Mathematical model for the control of measles. J Appl Sci Environ Manag 22(4):571–576
Qureshi S et al (2020) Monotonically decreasing behavior of measles epidemic well captured by Atangana–Baleanu–Caputo fractional operator under real measles data of Pakistan. Chaos Solitons Fractals 131:109478
Ashraf F, Ahmad M (2019) Nonstandard finite difference scheme for control of measles epidemiology. Int J Adv Appl Sci 6(3):79–85
System BRFS et al (2017) Centers for disease control and prevention. https://www.cdc.gov/brfss/annual_data/annual_2016.html. Published 6 Dec 2017. Accessed 21 May
Diekmann O, Heesterbeek JAP, Metz JA (1990) On the definition and the computation of the basic reproduction ratio r 0 in models for infectious diseases in heterogeneous populations. J Math Biol 28(4):365–382
Steele J (2004) An introduction to the art of mathematical inequalities. The Cauchy–Schwarz master class MAA problem books series. Mathematical Association of America, Washington, DC
LaSalle J (1976) The stability of dynamical systems, regional conference series in applied mathematics. SIAM, Philadelphia, Khalid Hattaf Department of Mathematics and Computer Science. Hassan II University, PO Box, Faculty of Sciences Ben M’sik, p 7955
James Peter O, Ojo MM, Viriyapong R, Abiodun Oguntolu F (2022) Mathematical model of measles transmission dynamics using real data from Nigeria. J Differ Equ Appl. https://doi.org/10.1080/10236198.2022.2079411
Marino S, Hogue IB, Ray CJ, Kirschner DE (2008) A methodology for performing global uncertainty and sensitivity analysis in systems biology. J Theor Biol 254(1):178–196. https://doi.org/10.1016/j.jtbi.2008.04.011
Saltelli A (2002) Making best use of model evaluations to compute sensitivity indices. Comput Phys Commun 145(2):280–297. https://doi.org/10.1016/S0010-4655(02)00280-1
Saltelli A, Annoni P, Azzini I, Campolongo F, Ratto M, Tarantola S (2010) Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index. Comput Phys Commun 181(2):259–270. https://doi.org/10.1016/j.cpc.2009.09.018
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
All authors contributed equally to this work. All authors have read and agreed to the proofs of the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
There are no conflicts of interest to declare.
Code Availability
The code that support the findings of this study are available from the corresponding author upon reasonable request.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Peter, O.J., Panigoro, H.S., Ibrahim, M.A. et al. Analysis and dynamics of measles with control strategies: a mathematical modeling approach. Int. J. Dynam. Control 11, 2538–2552 (2023). https://doi.org/10.1007/s40435-022-01105-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40435-022-01105-1