In this article, the Caputo fractional derivative operator of different orders $ 0 < \alpha\leq1 $ is applied to formulate the fractional-order model of the COVID-19 pandemic. The existence and boundedness of the solutions of the model are investigated by using the Gronwall-Bellman inequality. Further, the uniqueness of the model solutions is established by using the fixed-point theory. The Laplace Adomian decomposition method is used to obtain an approximate solution of the nonlinear system of fractional-order differential equations of the model with a different fractional-order $ \alpha $ for every compartment in the model. Finally, graphical presentations are presented to show the effects of other fractional parameters $ \alpha $ on the obtained approximate solutions.
Citation: Ihtisham Ul Haq, Nigar Ali, Hijaz Ahmad, Taher A. Nofal. On the fractional-order mathematical model of COVID-19 with the effects of multiple non-pharmaceutical interventions[J]. AIMS Mathematics, 2022, 7(9): 16017-16036. doi: 10.3934/math.2022877
In this article, the Caputo fractional derivative operator of different orders $ 0 < \alpha\leq1 $ is applied to formulate the fractional-order model of the COVID-19 pandemic. The existence and boundedness of the solutions of the model are investigated by using the Gronwall-Bellman inequality. Further, the uniqueness of the model solutions is established by using the fixed-point theory. The Laplace Adomian decomposition method is used to obtain an approximate solution of the nonlinear system of fractional-order differential equations of the model with a different fractional-order $ \alpha $ for every compartment in the model. Finally, graphical presentations are presented to show the effects of other fractional parameters $ \alpha $ on the obtained approximate solutions.
[1] | M. Garcia, N. Lipskiy, J. Tyson, R. Watkins, E. Stein, T. Kinley, Centers for disease control and prevention 2019 novel coronavirus disease (COVID-19) information management: Addressing national health-care and public health needs for standardized data definitions and codified vocabulary for data exchange, J. Am. Med. Inf. Assoc., 27 (2020), 1476–1487. https://doi.org/10.1093/jamia/ocaa141 doi: 10.1093/jamia/ocaa141 |
[2] | Report 9–Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, MRC Centre for Global Infectious Disease Analysis COVID-19, 2020. Available from: https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-9-impact-of-npis-on-covid-19/. |
[3] | P. Roy, K. R. Upadhyay, J. Caur, Modeling Zika transmission dynamics: Prevention and control, J. Biol. Syst., 28 (2020), 719–749. https://doi.org/10.1142/S021833902050014X doi: 10.1142/S021833902050014X |
[4] | S. Dilshad, N. Singh, M. Atif, A. Hanif, N. Yaqub, W. A. Farooq, et al., Automated image classification of chest X-rays of COVID-19 using deep transfer learning, Results Phys., 28 (2021), 104529. https://doi.org/10.1016/j.rinp.2021.104529 doi: 10.1016/j.rinp.2021.104529 |
[5] | M. Nicola, Z. Alsafi, C. Sohrabi, A. Kerwan, A. Al-Jabir, C. Iosifidis, et al., The socio-economic implications of the coronavirus pandemic (COVID-19): A review, Int. J. Surg., 78 (2020), 185–193. https://doi.org/10.1016/j.ijsu.2020.04.018 doi: 10.1016/j.ijsu.2020.04.018 |
[6] | I. A. Bashir, B. A. Nasidi, Fractional order model for the role of mild cases in the transmission of COVID-19, Chaos Solition. Fract., 142 (2021), 110374–110383. https://doi.org/10.1016/j.chaos.2020.110374 doi: 10.1016/j.chaos.2020.110374 |
[7] | S. Ahmada, A. Ullaha, Q. Mdallal, H. Khan, K. Shaha, A. Khan, Fractional order mathematical modeling of COVID-19 transmission, Chaos Solition. Fract., 139 (2020), 110256–110263. https://doi.org/10.1016/j.chaos.2020.110256 doi: 10.1016/j.chaos.2020.110256 |
[8] | T. Chen, J. Rui, Q. Wang, Z. Zhao, J. Cui, L. Yin, A mathematical model for simulating the phase-based transmissibility of a novel coronavirus, Infect. Dis. Poverty, 9 (2020), 24. https://doi.org/10.1186/s40249-020-00640-3 doi: 10.1186/s40249-020-00640-3 |
[9] | K. Nisar, S. Ahmad, A. Ullah, K. Shah, H. Alrabaiahc, M. Arfana, Mathematical analysis of SIRD model of COVID-19 with Caputo fractional derivative based on real data, Results Phys., 21 (2021), 103772–103780. https://doi.org/10.1016/j.rinp.2020.103772 doi: 10.1016/j.rinp.2020.103772 |
[10] | A. J. Mumbu, A. K. Hugo, Mathematical modelling on COVID-19 transmission impacts with preventive measures: A case study of Tanzania, Adv. Differ. Equ., 14 (2020), 748–766. https://doi.org/10.1080/17513758.2020.1823494 doi: 10.1080/17513758.2020.1823494 |
[11] | R. Verma, S. P. Tiwari, R. Upadhyay, Transmission dynamics of epidemic spread and outbreak of Ebola in West Africa: Fuzzy modeling and simulation, J. Biol. Dyn., 60 (2019), 637–671. https://doi.org/10.1007/s12190-018-01231-0 doi: 10.1007/s12190-018-01231-0 |
[12] | M. A. Khan, S. Ullah, K. O. Okosun, K. Shah, A fractional order pine wilt disease model with Caputo-Fabrizio derivative, Adv. Differ. Equ., 2018 (2018), 410. https://doi.org/10.1186/s13662-018-1868-4 doi: 10.1186/s13662-018-1868-4 |
[13] | I. Area, H. Batarfi, J. Losada, J. J. Nieto, W. Shammakh, Á. Torres, On a fractional order Ebola epidemic model, Adv. Differ. Equ., 2015 (2015), 278. https://doi.org/10.1186/s13662-015-0613-5 doi: 10.1186/s13662-015-0613-5 |
[14] | M. Dulǎu, A. Gligor, T. M. Dulău, Fractional order controllers versus integer order controllers, Procedia Eng., 181 (2017), 538–545. https://doi.org/10.1016/j.proeng.2017.02.431 doi: 10.1016/j.proeng.2017.02.431 |
[15] | D. Sain, B. M. Mohan, A simple approach to mathematical modelling of integer order and fractional order fuzzy PID controllers using one-dimensional input space and their experimental realization, J. Franklin Inst., 358 (2021), 3726–3756. https://doi.org/10.1016/j.jfranklin.2021.03.010 doi: 10.1016/j.jfranklin.2021.03.010 |
[16] | M. Higazy, Novel fractional order SIDARTHE mathematical model of COVID-19 pandemic, Chaos Solition. Fract., 138 (2020), 110007. https://doi.org/10.1016/j.chaos.2020.110007 doi: 10.1016/j.chaos.2020.110007 |
[17] | N. H. Tuan, H. Mohammadi, S. Rezapour, A mathematical model for COVID-19 transmission by using the Caputo fractional derivative, Chaos Solition. Fract., 140 (2020), 110107. https://doi.org/10.1016/j.chaos.2020.110107 doi: 10.1016/j.chaos.2020.110107 |
[18] | A. Srivastav, P. Tiwari, P. Srivastava, M. Ghosh, Y. Kang, A mathematical model for the impacts of face mask, hospitalization and quarantine on the dynamics of COVID-19 in India: Deterministic vs. stochastic, Math. Biosci. Eng., 18 (2021), 182–213. https://doi.org/10.3934/mbe.2021010 doi: 10.3934/mbe.2021010 |
[19] | K. Shah, T. A. jawad, I. Mahariq, F. Jarad, Qualitative analysis of a mathematical model in the time of COVID-19, BioMed Res. Int., 2020 (2020), 5098598. https://doi.org/10.1155/2020/5098598 doi: 10.1155/2020/5098598 |
[20] | Z. Zhang, A. Zeb, O. F. Egbelowo, V. S. Erturk, Dynamics of a fractional order mathematical model for COVID-19 epidemic, Adv. Differ. Equ., 2020 (2020), 420. https://doi.org/10.1186/s13662-020-02873-w doi: 10.1186/s13662-020-02873-w |
[21] | H. Jafari, C. M. Khalique, M. Nazari, Application of the Laplace decomposition method for solving linear and nonlinear fractional diffusion–wave equations, Appl. Math. Lett., 24 (2011), 1799–1805. https://doi.org/10.1016/j.aml.2011.04.037 doi: 10.1016/j.aml.2011.04.037 |
[22] | F. Haq, K. Shah, G. Rahman, M. Shahzada, Numerical solution of fractional order smoking model via Laplace Adomian decomposition method, Alex. Eng. J., 57 (2018), 1061–1069. https://doi.org/10.1016/j.aej.2017.02.015 doi: 10.1016/j.aej.2017.02.015 |
[23] | M. Z. Mohamed, T. M. Elzaki, Comparison between the Laplace decomposition method and Adomian decomposition in time-space fractional nonlinear fractional differential equations, Appl. Math., 9 (2018), 84309. https://doi.org/10.4236/am.2018.94032 doi: 10.4236/am.2018.94032 |
[24] | M. De la Sen, Positivity and stability of the solutions of Caputo fractional linear time-invariant systems of any order with internal point delays, Abstr. Appl. Anal., 2011 (2011), 161246. https://doi.org/10.1155/2011/161246 doi: 10.1155/2011/161246 |
[25] | S. Bushnaq, T. Saeed, D. F. M. Torres, A. Zeb, Control of COVID-19 dynamics through a fractional-order model, Alex. Eng. J., 60 (2021), 3587–3592. https://doi.org/10.1016/j.aej.2021.02.022 doi: 10.1016/j.aej.2021.02.022 |
[26] | R. Magin, Fractional calculus in bioengineering, Crit. Rev. Biomed. Eng., 32 (2006), 1–104. https://doi.org/10.1615/critrevbiomedeng.v32.i1.10 doi: 10.1615/critrevbiomedeng.v32.i1.10 |
[27] | Introduction to Differential Equations, The Hong Kong University of Science and Technology, 2003. Available from: https://hostnezt.com/cssfiles/appliedmaths/Introduction20to20Differential20Equations20By20Jeffrey20R.0Chasnov.pdf. |
[28] | I. Podlubny, A. Chechkin, T. Skovranek, Y. Q. Chen, M. V. Jara, Matrix approach to discrete fractional calculus Ⅱ: Partial fractional differential equations, J. Comput. Phys., 228 (1019), 3137–3153. https://doi.org/10.1016/j.jcp.2009.01.014 doi: 10.1016/j.jcp.2009.01.014 |
[29] | J. Sabatier, O. P. Agrawal, J. A. Tenreiro Machado, Advances in fractional calculus, Theoretical Developments and Applications in Physics and Engineering, 4 Eds., Berlin: Springer, 2007. https://doi.org/10.1007/978-1-4020-6042-7 |
[30] | M. S. Abdo, K. Shah, H. A. Wahash, S. K. Panchal, On a comprehensive model of the novel coronavirus (COVID-19) under Mittag-Leffler derivative, Chaos Solition. Fract., 135 (2020), 109867. https://doi.org/10.1016/j.chaos.2020.109867 doi: 10.1016/j.chaos.2020.109867 |
[31] | S. Kumar, A. Yildirim, Y. Khan, L. Wei, A fractional model of the diffusion equation and its analytical solution using Laplace transform, Sci. Iran., 19 (2012), 1117–1123. https://doi.org/10.1016/j.scient.2012.06.016 doi: 10.1016/j.scient.2012.06.016 |
[32] | H. Khan, R. Shah, P. Kumam, D. Baleanu, M. Arif, A two-step Laplace decomposition method for solving nonlinear partial differential equations, Int. J. Phys. Sci., 6 (2011), 4102–4109. https://doi.org/10.5897/IJPS11.146 doi: 10.5897/IJPS11.146 |
[33] | J. H. He, Variational iteration method–a kind of non-linear analytical technique: Some examples, Int. J. Non-Linear Mech., 34 (1999), 699–708. https://doi.org/10.1016/S0020-7462(98)00048-1 doi: 10.1016/S0020-7462(98)00048-1 |
[34] | D. Aldila, M. Z. Ndii, B. M. Samiadji, Optimal control on COVID-19 eradication program in Indonesia under the effect of community awareness, Math. Biosci. Eng., 17 (2020), 6355–6389. http://dx.doi.org/10.3934/mbe.2020335 doi: 10.3934/mbe.2020335 |
[35] | A. Davies, K. Thompson, K. Giri, G. Kafatos, J. Walker, A. Bennett, Testing the efficacy of homemade masks: Would they protect in an influenza pandemic, Disaster Med. Public Health Prep., 7 (2013), 413–418. https://doi.org/10.1017/dmp.2013.43 doi: 10.1017/dmp.2013.43 |
[36] | C. J. Noakes, P. Sleigh, Mathematical models for assessing the role of airflow on the risk of airborne infection in hospital wards, J. R. Soc. Interface, 6 (2009), S791–S800. https://doi.org/10.1098/rsif.2009.0305.focus doi: 10.1098/rsif.2009.0305.focus |
[37] | M. A. Khan, A. Atangana, Modeling the dynamics of novel coronavirus (2019-nCov) with fractional derivative, Alex. Eng. J., 59 (2020), 2379–2389. https://doi.org/10.1016/j.aej.2020.02.033 doi: 10.1016/j.aej.2020.02.033 |
[38] | F. Zhou, T. Yu, R. Du, G. Fan, Y. Liu, Z. Liu, et al., Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study, Lancet, 395 (2020), 1054–1062. https://doi.org/10.1016/S0140-6736(20)30566-3 doi: 10.1016/S0140-6736(20)30566-3 |
[39] | B. Tang, X. Wang, Q. Li, N. L. Bragazzi, S. Tang, Y. Xiao, et al., Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions, J. Clin. Med., 9 (2020), 462. https://doi.org/10.3390/jcm9020462 doi: 10.3390/jcm9020462 |