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A novel numerical dynamics of fractional derivatives involving singular and nonsingular kernels: designing a stochastic cholera epidemic model

  • Received: 16 August 2022 Revised: 30 October 2022 Accepted: 10 November 2022 Published: 22 November 2022
  • MSC : 46S40, 47H10, 54H25

  • In this research, we investigate the direct interaction acquisition method to create a stochastic computational formula of cholera infection evolution via the fractional calculus theory. Susceptible people, infected individuals, medicated individuals, and restored individuals are all included in the framework. Besides that, we transformed the mathematical approach into a stochastic model since it neglected the randomization mechanism and external influences. The descriptive behaviours of systems are then investigated, including the global positivity of the solution, ergodicity and stationary distribution are carried out. Furthermore, the stochastic reproductive number for the system is determined while for the case $ \mathbb{R}_{0}^{s} > 1, $ some sufficient condition for the existence of stationary distribution is obtained. To test the complexity of the proposed scheme, various fractional derivative operators such as power law, exponential decay law and the generalized Mittag-Leffler kernel were used. We included a stochastic factor in every case and employed linear growth and Lipschitz criteria to illustrate the existence and uniqueness of solutions. So every case was numerically investigated, utilizing the newest numerical technique. According to simulation data, the main significant aspects of eradicating cholera infection from society are reduced interaction incidence, improved therapeutic rate, and hygiene facilities.

    Citation: Saima Rashid, Fahd Jarad, Hajid Alsubaie, Ayman A. Aly, Ahmed Alotaibi. A novel numerical dynamics of fractional derivatives involving singular and nonsingular kernels: designing a stochastic cholera epidemic model[J]. AIMS Mathematics, 2023, 8(2): 3484-3522. doi: 10.3934/math.2023178

    Related Papers:

  • In this research, we investigate the direct interaction acquisition method to create a stochastic computational formula of cholera infection evolution via the fractional calculus theory. Susceptible people, infected individuals, medicated individuals, and restored individuals are all included in the framework. Besides that, we transformed the mathematical approach into a stochastic model since it neglected the randomization mechanism and external influences. The descriptive behaviours of systems are then investigated, including the global positivity of the solution, ergodicity and stationary distribution are carried out. Furthermore, the stochastic reproductive number for the system is determined while for the case $ \mathbb{R}_{0}^{s} > 1, $ some sufficient condition for the existence of stationary distribution is obtained. To test the complexity of the proposed scheme, various fractional derivative operators such as power law, exponential decay law and the generalized Mittag-Leffler kernel were used. We included a stochastic factor in every case and employed linear growth and Lipschitz criteria to illustrate the existence and uniqueness of solutions. So every case was numerically investigated, utilizing the newest numerical technique. According to simulation data, the main significant aspects of eradicating cholera infection from society are reduced interaction incidence, improved therapeutic rate, and hygiene facilities.



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    [1] I. Podlubny, Fractional differential equations, San Diego: Academic Press, 1999.
    [2] S. N. Hajiseyedazizi, M. E. Samei, J. Alzabut, Y. M. Chu, On multi-step methods for singular fractional q-integro-differential equations, Open Math., 19 (2021), 1378–1405. https://doi.org/10.1515/math-2021-0093 doi: 10.1515/math-2021-0093
    [3] K. M. Owolabi, Z. Hammouch, Spatiotemporal patterns in the Belousov-Zhabotinskii reaction systems with Atangana-Baleanu fractional order derivative, Phys. A, 523 (2019), 1072–1090. https://doi.org/10.1016/j.physa.2019.04.017 doi: 10.1016/j.physa.2019.04.017
    [4] S. Rashid, A. Khalid, S. Sultana, F. Jarad, K. M. Abualnaja, Y. S. Hamed, Novel numerical investigation of the fractional oncolytic effectiveness model with M1 virus via generalized fractional derivative with optimal criterion, Results Phys., 37 (2022), 105553. https://doi.org/10.1016/j.rinp.2022.105553 doi: 10.1016/j.rinp.2022.105553
    [5] F. Z. Wang, M. N. Khan, I. Ahmad, H. Ahmad, H. Abu-Zinadah, Y. M. Chu, Numerical solution of traveling waves in chemical kinetics: time-fractional Fishers equations, Fractals, 30 (2022), 2240051. https://doi.org/10.1142/S0218348X22400515 doi: 10.1142/S0218348X22400515
    [6] O. A. Arqub, M. Al-Smadi, Atangana-Baleanu fractional approach to the solutions of BagleyTorvik and PainlevE¸ equations in Hilbert space, Chaos Solitons Fract., 117 (2018), 161–167. https://doi.org/10.1016/j.chaos.2018.10.013 doi: 10.1016/j.chaos.2018.10.013
    [7] M. Caputo, M. Fabrizio, A new definition of fractional derivative without singular kernel, Progr. Fract. Differ. Appl., 2 (2015), 73–85.
    [8] A. Atangana, D. Baleanu, New fractional derivatives with non-local and non-singular kernel theory and application to heat transfer model, Therm. Sci., 20 (2016), 763–769.
    [9] S. Rashid, S. Sultana, Y. Karaca, A. Khalid, Y. M. Chu, Some further extensions considering discrete proportional fractional operators, Fractals, 30 (2022), 2240026. https://doi.org/10.1142/S0218348X22400266 doi: 10.1142/S0218348X22400266
    [10] S. Rashid, E. I. Abouelmagd, A. Khalid, F. B. Farooq, Y. M. Chu, Some recent developments on dynamical h-discrete fractional type inequalities in the frame of nonsingular and nonlocal kernels, Fractals, 30 (2022), 2240110. https://doi.org/10.1142/S0218348X22401107 doi: 10.1142/S0218348X22401107
    [11] S. Rashid, E. I. Abouelmagd, S. Sultana, Y. M. Chu, New developments in weighted n-fold type inequalities via discrete generalized h-proportional fractional operators, Fractals, 30 (2022), 2240056. https://doi.org/10.1142/S0218348X22400564 doi: 10.1142/S0218348X22400564
    [12] M. Al-Qurashi, S. Rashid, S. Sultana, F. Jarad, A. M. Alsharif, Fractional-order partial differential equations describing propagation of shallow water waves depending on power and Mittag-Leffler memory, AIMS Math., 7 (2022), 12587–12619. https://doi.org/10.3934/math.2022697 doi: 10.3934/math.2022697
    [13] S. Rashid, R. Ashraf, F. Jarad, Strong interaction of Jafari decomposition method with nonlinear fractional-order partial differential equations arising in plasma via the singular and nonsingular kernels, AIMS Math., 7 (2022), 7936–7963. https://doi.org/10.3934/math.2022444 doi: 10.3934/math.2022444
    [14] S. Rashid, F. Jarad, A. G. Ahmad, K. M. Abualnaja, New numerical dynamics of the heroin epidemic model using a fractional derivative with Mittag-Leffler kernel and consequences for control mechanisms, Results Phys., 35 (2022), 105304. https://doi.org/10.1016/j.rinp.2022.105304 doi: 10.1016/j.rinp.2022.105304
    [15] S. A. Iqbal, M. G. Hafez, Y. M. Chu, C. Park, Dynamical analysis of nonautonomous RLC circuit with the absence and presence of Atangana-Baleanu fractional derivativae, J. Appl. Anal. Comput., 12 (2022), 770–789.
    [16] P. Waltman, Deterministic threshold models in the theory of epidemics, New York: Springer-Verlag, 1974. https://doi.org/10.1007/978-3-642-80820-3
    [17] L. Arnold, Stochastic differential equations: theory and applications, Wiley, 1974.
    [18] A. Friedman, Stochastic differential equations and applications, Vol. 1, Academic Press, 1975.
    [19] A. C. J. Luo, V. Afraimovich, Long-range interactions, stochasticity and fractional dynamics: dedicated to George M. Zaslavsky (1935–2008), Springer, 2011.
    [20] A. G. Ladde, G. S. Ladde, Dynamic processes under random environment, Bull. Marathwada Math. Soc., 8 (2007), 96–123.
    [21] R. J. Elliott, Stochastic calculus and applications, New York: Springer Verlag, 1982.
    [22] G. S. Ladde, L. Wu, Stochastic modeling and statistical analysis on the stock price processes, Nonlinear Anal.: Theory Methods, 71 (2009), 1203–1208.
    [23] G. S. Ladde, L. Wu, Development of nonlinear stochastic models by using stock price data and basic statistics, Neural Parallel Sci. Comput., 18 (2010), 269–282.
    [24] S. Rashid, M. K. Iqbal, A. M. Alshehri, R. Ashraf, F. Jarad, A comprehensive analysis of the stochastic fractal-fractional tuberculosis model via Mittag-Leffler kernel and white noise, Results Phys., 39 (2022), 105764. https://doi.org/10.1016/j.rinp.2022.105764 doi: 10.1016/j.rinp.2022.105764
    [25] S. Rashid, R. Ashraf, Q. Ul-Ain Asif, F. Jarad, Novel dynamics of a stochastic fractal-fractional immune effector response to viral infection via latently infectious tissues, Math. Biosci. Eng., 19 (2022), 11563–11594. https://doi.org/10.3934/mbe.2022539 doi: 10.3934/mbe.2022539
    [26] P. S. Brachman, E. Abrutyn, Bacterial infections of humans: epidemiology and control, New York: Springer, 2009.
    [27] Centers for Disease Control and Prevention, Cholera–Vibrio cholerae infection, 2020. Available from: https://www.cdc.gov/cholera/index.html.
    [28] World Health Organization, C. L. Chaignat, 10 facts about cholera, 2017. Available from: https://borgenproject.org/10-facts-cholera/.
    [29] C. T. Codeco, Endemic and epidemic dynamics of cholera: the role of the aquatic reservoir, BMC Infect. Dis., 1 (2001), 1–14.
    [30] E. Bertuzzo, S. Azaele, A. Maritan, M. Gatto, I. RodriguezIturbe, A. Rinaldo, On the space-time evolution of a cholera epidemic, Water Resour. Res., 44 (2008), 1–8. https://doi.org/10.1029/2007WR006211 doi: 10.1029/2007WR006211
    [31] E. Bertuzzo, R. Casagrandi, M. Gatto, I. Rodriguez-Iturbe, A. Rinaldo, On spatially explicit models of cholera epidemics, J. Roy. Soc. Interface, 7 (2010), 321–333. https://doi.org/10.1098/rsif.2009.0204 doi: 10.1098/rsif.2009.0204
    [32] L. Mari, E. Bertuzzo, L. Righetto, Modelling cholera epidemics: the role of waterways, human mobility and sanitation, J. Roy. Soc. Interface, 9 (2012), 376–388. https://doi.org/10.1098/rsif.2011.0304 doi: 10.1098/rsif.2011.0304
    [33] A. A. Ayoade, M. O. Ibrahim, O. J. Peter, F. A. Oguntolu, On the global stability of cholera model with prevention and control, Malays. J. Comput., 3 (2018), 28–36.
    [34] C. Ratchford, J. Wang, Modeling cholera dynamics at multiple scales: environmental evolution, between-host transmission, and within-host interaction, Math. Biosci. Eng., 16 (2019), 782–812. https://doi.org/10.3934/mbe.2019037 doi: 10.3934/mbe.2019037
    [35] A. Kumar, M. Kumar, Nilam, A study on the stability behavior of an epidemic model with ratio-dependent incidence and saturated treatment, Theory Biosci., 139 (2020), 225–234. https://doi.org/10.1007/s12064-020-00314-6 doi: 10.1007/s12064-020-00314-6
    [36] M. Al-Adydah, A. Mwasa, J. M. Tchuenche, R. J. Smith, Modeling cholera disease with education and chlorination, J. Biol. Syst., 21 (2013), 1340007. https://doi.org/10.1142/S021833901340007X doi: 10.1142/S021833901340007X
    [37] V. D. Nguyen, N. Sreenivasan, E. Lam, T. Ayers, D. Kargbo, F. Dafae, et al., Cholera epidemic associated with consumption of unsafe drinking water and street-vended water-eastern freetown, Sierra Leone, 2012, Am. J. Trop. Med. Hyg., 90 (2014), 518–523. https://doi.org/10.4269/ajtmh.13-0567 doi: 10.4269/ajtmh.13-0567
    [38] J. G. Liu, X. J. Yang, Y. Y. Feng, L. L. Geng, Fundamental results to the weighted Caputo-type differential operator, Appl. Math. Lett., 121 (2021), 107421. https://doi.org/10.1016/j.aml.2021.107421 doi: 10.1016/j.aml.2021.107421
    [39] T. H. Zhao, O. Castillo, H. Jahanshahi, A. Yusuf, M. O. Alassafi, F. E. Alsaadi, et al., A fuzzy-based strategy to suppress the novel coronavirus (2019-NCOV) massive outbreak, Appl. Comput. Math., 20 (2021), 160–176.
    [40] T. H. Zhao, M. I. Khan, Y. M. Chu, Artificial neural networking (ANN) analysis for heat and entropy generation in flow of non-Newtonian fluid between two rotating disks, Math. Methods Appl. Sci., 2021. https://doi.org/10.1002/mma.7310
    [41] J. G. Liu, X. J. Yang, L. L. Geng, Y. R. Fan, Group analysis of the time fractional $(3+1)$-dimensional KDV-type equation, Fractals, 29 (2021), 2150169. https://doi.org/10.1142/S0218348X21501693 doi: 10.1142/S0218348X21501693
    [42] S. Hussain, E. N. Madi, H. Khan, S. Etemad, S. Rezapour, T. Sitthiwirattham, et al., Investigation of the stochastic modeling of COVID-19 with environmental noise from the analytical and numerical point of view, Mathematics, 9 (2021), 3122. https://doi.org/10.3390/math9233122 doi: 10.3390/math9233122
    [43] K. Karthikeyan, P. Karthikeyan, H. M. Baskonus, K. Venkatachalam, Y. M. Chu, Almost sectorial operators on $\Psi$-Hilfer derivative fractional impulsive integro-differential equations, Math. Methods Appl. Sci., 2021 (2021), 8045–8059. https://doi.org/10.1002/mma.7954 doi: 10.1002/mma.7954
    [44] Y. M. Chu, U. Nazir, M. Sohail, M. M. Selim, J. R. Lee, Enhancement in thermal energy and solute particles using hybrid nanoparticles by engaging activation energy and chemical reaction over a parabolic surface via finite element approach, Fractal Fract., 5 (2021), 119. https://doi.org/10.3390/fractalfract5030119 doi: 10.3390/fractalfract5030119
    [45] S. Hussain, E. N. Madi, H. Khan, H. Gulzar, S. Etemad, S. Rezapour, M. K. A. Kaabar, On the stochastic modeling of COVID-19 under the environmental white noise, J. Function Spaces, 2022 (2022), 4320865. https://doi.org/10.1155/2022/4320865 doi: 10.1155/2022/4320865
    [46] M. Ahmad, A. Zada, M. Ghaderi, R. George, S. Rezapour, On the Existence and stability of a neutral stochastic fractional differential system, Fractal Fract., 6 (2022), 203. https://doi.org/10.3390/fractalfract6040203 doi: 10.3390/fractalfract6040203
    [47] G. T. Tilahun, W. A. Woldegerima, A. Wondifraw, Stochastic and deterministic mathematical model of cholera disease dynamics with direct transmission, Adv. Differ. Equ., 2020 (2020), 670 https://doi.org/10.1186/s13662-020-03130-w doi: 10.1186/s13662-020-03130-w
    [48] Y. Zhang, Y. Li, Q. Zhang, A. Li, Behavior of a stochastic SIR epidemic model with saturated incidence and vaccination rules, Phys. A, 501 (2018), 178–187. https://doi.org/10.1016/j.physa.2018.02.191 doi: 10.1016/j.physa.2018.02.191
    [49] N. Sene, Analysis of the stochastic model for predicting the novel coronavirus disease, Adv. Differ. Equ., 2020 (2020), 568. https://doi.org/10.1186/s13662-020-03025-w doi: 10.1186/s13662-020-03025-w
    [50] R. Khasminskii, Stochastic stability of differential equations, Berlin: Springer, 2012.
    [51] A. Atangana, S. I. Araz, New numerical method for ordinary differential equations: Newton polynomial, J. Comput. Appl. Math., 372 (2020), 112622. https://doi.org/10.1016/j.cam.2019.112622 doi: 10.1016/j.cam.2019.112622
    [52] M. Toufik, A. Atangana, New numerical approximation of fractional derivative with non-local and non-singular kernel: application to chaotic models, Eur. Phys. J. Plus, 132 (2017), 444. https://doi.org/10.1140/epjp/i2017-11717-0 doi: 10.1140/epjp/i2017-11717-0
    [53] E. A. Kamuhanda, S. Osman, M. Wainaina, Mathematical modelling and analysis of the dynamics of cholera, Global J. Pure Appl. Math., 14 (2018), 1259–1275.
    [54] M. O. Beryl, L. O. George, N. O. Fredrick, Mathematical analysis of a cholera transmission model incorporating media coverage, Int. J. Pure Appl. Math., 111 (2016), 219–231.
    [55] S. Fatima, I. Krishnarajah, M. Z. A. M. Jaffar, M. B. Adam, A mathematical model for the control of cholera in Nigeria, Res. J. Environ. Earth Sci., 6 (2014), 321–325.
    [56] A. P. Lemos-Paiao, C. J. Silva, D. F. M. Torres, A cholera mathematical model with vaccination and the biggest outbreak of world's history, AIMS Math., 3 (2018), 448–463. https://doi.org/10.3934/Math.2018.4.448 doi: 10.3934/Math.2018.4.448
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