Research article

A discrete-time mathematical model for mosaic disease dynamics in cassava: Neimark-Sacker bifurcation and sensitivity analysis

  • Published: 13 August 2025
  • MSC : 39A22, 39A28, 39A30

  • Cassava mosaic disease remains a significant threat to cassava production, leading to severe yield losses and food insecurity. While several continuous-time models have been proposed to understand cassava mosaic disease transmission, there is limited understanding of cassava mosaic disease behavior in discrete-time settings. Discrete-time models are often easier to apply in agricultural settings, as they align more naturally with seasonal planting schedules and data collection intervals. To address this, we developed and analyzed a novel discrete-time mathematical model that captured the complex dynamics of cassava mosaic disease transmission via whitefly vectors. We introduced a density-dependent modification theorem for the nonnegativity and discussed the boundedness of solutions. The basic reproduction number was derived, and the stability of the disease-free equilibrium was examined. Additionally, we investigated the existence and stability of endemic fixed points. We conducted an analytical study of the Neimark-Sacker bifurcation using a novel approach without eigenvalues. Furthermore, we performed a comprehensive sensitivity analysis of our discrete model using Sobol indices. Numerical simulations validated our analytical findings and illustrated the impact of various parameters on the stability of fixed points. We also presented stability regions in different parameter planes. Our findings emphasized that elevated infection rates contributed to seasonal outbreaks of cassava mosaic disease. Furthermore, effective management of both plant infection rates and vector abundance was essential for controlling the disease. Finally, our results were consistent with those obtained from continuous models.

    Citation: Selim Reja, Fahad Al Basir, Khalid Aldawsari. A discrete-time mathematical model for mosaic disease dynamics in cassava: Neimark-Sacker bifurcation and sensitivity analysis[J]. AIMS Mathematics, 2025, 10(8): 18295-18320. doi: 10.3934/math.2025817

    Related Papers:

  • Cassava mosaic disease remains a significant threat to cassava production, leading to severe yield losses and food insecurity. While several continuous-time models have been proposed to understand cassava mosaic disease transmission, there is limited understanding of cassava mosaic disease behavior in discrete-time settings. Discrete-time models are often easier to apply in agricultural settings, as they align more naturally with seasonal planting schedules and data collection intervals. To address this, we developed and analyzed a novel discrete-time mathematical model that captured the complex dynamics of cassava mosaic disease transmission via whitefly vectors. We introduced a density-dependent modification theorem for the nonnegativity and discussed the boundedness of solutions. The basic reproduction number was derived, and the stability of the disease-free equilibrium was examined. Additionally, we investigated the existence and stability of endemic fixed points. We conducted an analytical study of the Neimark-Sacker bifurcation using a novel approach without eigenvalues. Furthermore, we performed a comprehensive sensitivity analysis of our discrete model using Sobol indices. Numerical simulations validated our analytical findings and illustrated the impact of various parameters on the stability of fixed points. We also presented stability regions in different parameter planes. Our findings emphasized that elevated infection rates contributed to seasonal outbreaks of cassava mosaic disease. Furthermore, effective management of both plant infection rates and vector abundance was essential for controlling the disease. Finally, our results were consistent with those obtained from continuous models.



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    [1] M. Chapwanya, Y. Dumont, Application of mathematical epidemiology to crop vector-borne diseases: The cassava mosaic virus disease case, In: Infectious Diseases and our planet, Cham: Springer, 2021, 57–95. https://doi.org/10.1007/978-3-030-50826-5_4
    [2] R. Bhaargavi, T. K. S. Latha, T. Makeshkumar, S. Harish, Cassava mosaic disease: strategies for recovery and sustainable management, Australasian Plant Pathol., 54 (2025), 1–12. https://doi.org/10.1007/s13313-024-01014-1 doi: 10.1007/s13313-024-01014-1
    [3] J. Legg, S. Winter, Cassava mosaic viruses (Geminiviridae), Encyclopedia of Virology (Fourth Edition), 3 (2021), 301–312. https://doi.org/10.1016/B978-0-12-809633-8.21523-9 doi: 10.1016/B978-0-12-809633-8.21523-9
    [4] O. Chase, I. Ferriol, J. J. López-Moya, Control of plant pathogenic viruses through interference with insect transmission, In: Plant virus-host interaction, 2 Eds., New Yourk: Academic Press, 2021,359–381. https://doi.org/10.1016/B978-0-12-821629-3.00019-1
    [5] K. M. G. Chanchala, Management of disease-transmitting insect vectors, In: Plant diseases and their management, New York: Apple Academic Press, 2024,191–220. https://doi.org/10.1201/9781032722856-7
    [6] D. Fargette, M. J. Jeger, C. Fauquet, L. D. C. Fishpool, Analysis of temporal disease progress of African cassava mosaic virus, Phytopathology, 84 (1994), 89–91. http://doi.org/10.1094/Phyto-84-91 doi: 10.1094/Phyto-84-91
    [7] E. W. Kitajima, An annotated list of plant viruses and viroids described in Brazil (1926–2018), Biota Neotrop., 20 (2020), v20n2. https://doi.org/10.1590/1676-0611-BN-2019-0932 doi: 10.1590/1676-0611-BN-2019-0932
    [8] A. G. Power, Virus spread and vector dynamics in genetically diverse plant populations, Ecology, 72 (1991), 232–241. https://doi.org/10.2307/1938917 doi: 10.2307/1938917
    [9] J. Navas-Castillo, E. Fiallo-Olivé, S. Sánchez-Campos, Emerging virus diseases transmitted by whiteflies, Annu. Rev. Phytopathol., 49 (2011), 219–248. https://doi.org/10.1146/annurev-phyto-072910-095235 doi: 10.1146/annurev-phyto-072910-095235
    [10] M. Abubakar, B. Koul, K. Chandrashekar, A. Raut, D. Yadav, Whitefly (Bemisia tabaci) management (WFM) strategies for sustainable agriculture: A review, Agriculture, 12 (2022), 1317. https://doi.org/10.3390/agriculture12091317 doi: 10.3390/agriculture12091317
    [11] J. Bird, K. Maramorosch, Viruses and virus diseases associated with whiteflies, Adv. Virus Res., 22 (1978), 55–110. https://doi.org/10.1016/S0065-3527(08)60772-1 doi: 10.1016/S0065-3527(08)60772-1
    [12] F. Al Basir, K. B. Blyuss, E. Venturino, Stability and bifurcation analysis of a multi-delay model for mosaic disease transmission, AIMS Mathematics, 8 (2023), 24545–24567. https://doi.org/10.3934/math.20231252 doi: 10.3934/math.20231252
    [13] M. Chapwanya, Y. Dumont, Application of mathematical epidemiology to crop vector-borne diseases: The cassava mosaic virus disease case, In: Infectious diseases and our planet, Cham: Springer, 2021, 57–95. https://doi.org/10.1007/978-3-030-50826-5_4
    [14] F. D. Magoyo, J. I. Irunde, D. Kuznetsov, Modeling the dynamics and transmission of cassava mosaic disease in Tanzania, Commun. Math. Biol. Neurosci., 2019 (2019), 4. https://doi.org/10.28919/cmbn/3819 doi: 10.28919/cmbn/3819
    [15] M. J. Jeger, J. Holt, F. Van Den Bosch, L. V. Madden, Epidemiology of insect-transmitted plant viruses: modelling disease dynamics and control interventions, Physiol. Entomol., 29 (2004), 291–304. https://doi.org/10.1111/j.0307-6962.2004.00394.x doi: 10.1111/j.0307-6962.2004.00394.x
    [16] S. Maity, P. S. Mandal, A comparison of deterministic and stochastic plant-vector-virus models based on probability of disease extinction and outbreak, Bull. Math. Biol., 84 (2022), 41. https://doi.org/10.1007/s11538-022-01001-x doi: 10.1007/s11538-022-01001-x
    [17] C. F. McQuaid, F. van den Bosch, A. Szyniszewska, T. Alicai, A. Pariyo, P. C. Chikoti, et al., Spatial dynamics and control of a crop pathogen with mixed-mode transmission. PLoS Comput. Biol., 13 (2017), e1005654. https://doi.org/10.1371/journal.pcbi.1005654 doi: 10.1371/journal.pcbi.1005654
    [18] Z. Lawrence, D. I. Wallace, The spatiotemporal dynamics of African cassava mosaic disease, In: BIOMAT 2010: International symposium on mathematical and computational biology, Singapore: World Scientific, 2011,236–255. https://doi.org/10.1142/9789814343435_0016
    [19] F. Al Basir, P. K. Roy, Dynamics of mosaic disease with roguing and delay in Jatropha curcas plantations, J. Appl. Math. Comput., 58 (2018), 1–31. https://doi.org/10.1007/s12190-017-1131-2 doi: 10.1007/s12190-017-1131-2
    [20] F. Al-Basir, P. K. Roy, S. Ray, Impact of roguing and insecticide spraying on mosaic disease in Jatropha curcas, Control Cybern., 46 (2017), 325–344.
    [21] F. Al Basir, Y. N. Kyrychko, K. B. Blyuss, S. Ray, Effects of vector maturation time on the dynamics of cassava mosaic disease. Bull. Math. Biol., 83 (2021), 87. https://doi.org/10.1007/s11538-021-00921-4 doi: 10.1007/s11538-021-00921-4
    [22] J. E. Franke, A. A. Yakubu, Disease-induced mortality in density-dependent discrete-time SIS epidemic models, J. Math. Biol., 57 (2008), 755–790. https://doi.org/10.1007/s00285-008-0188-9 doi: 10.1007/s00285-008-0188-9
    [23] C. Castillo-Chavez, A. A. Yakubu, Discrete-time S-I-S models with complex dynamics, Nonlinear Anal.-Theor., 47 (2001), 4753–4762. https://doi.org/10.1016/S0362-546X(01)00587-9 doi: 10.1016/S0362-546X(01)00587-9
    [24] M. Sekiguchi, E. Ishiwata, Global dynamics of a discretized SIRS epidemic model with time delay, J. Math. Anal. Appl., 371 (2010), 195–202. https://doi.org/10.1016/j.jmaa.2010.05.007 doi: 10.1016/j.jmaa.2010.05.007
    [25] L. J. S. Allen, A. M. Burgin, Comparison of deterministic and stochastic SIS and SIR models in discrete time, Math. Biosci., 163 (2000), 1–33. https://doi.org/10.1016/S0025-5564(99)00047-4 doi: 10.1016/S0025-5564(99)00047-4
    [26] J. Q. Li, Z. E. Ma, F. Brauer, Global analysis of discrete-time SI and SIS epidemic models, Math. Biosci. Eng., 4 (2007), 699–710. https://doi.org/10.3934/mbe.2007.4.699 doi: 10.3934/mbe.2007.4.699
    [27] Z. Y. Hu, Z. D. Teng, H. J. Jiang, Stability analysis in a class of discrete SIRS epidemic models, Nonlinear Anal.-Real, 13 (2012), 2017–2033. https://doi.org/10.1016/j.nonrwa.2011.12.024 doi: 10.1016/j.nonrwa.2011.12.024
    [28] L. J. Chen, L. J. Chen, Permanence of a discrete periodic Volterra model with mutual interference, Discrete Dyn. Nat. Soc., 2009 (2009), 205481. https://doi.org/10.1155/2009/205481 doi: 10.1155/2009/205481
    [29] J. Holt, M. J. Jeger, J. M. Thresh, G. W. Otim-Nape, An epidemilogical model incorporating vector population dynamics applied to African cassava mosaic virus disease, J. Appl. Ecol., 34 (1997), 793-806. https://doi.org/10.2307/2404924 doi: 10.2307/2404924
    [30] J. Chowdhury, F. Al Basir, A. Mukherjee, P. K. Roy, A theta logistic model for the dynamics of whitefly borne mosaic disease in Cassava: impact of roguing and insecticide spraying, J. Appl. Math. Comput., 71 (2025), 4897–4914. https://doi.org/10.1007/s12190-025-02419-x doi: 10.1007/s12190-025-02419-x
    [31] A. Columbu, R. D. Fuentes, S. Frassu, Uniform-in-time boundedness in a class of local and nonlocal nonlinear attraction-repulsion chemotaxis models with logistics, Nonlinear Anal.-Real, 79 (2024), 104135. https://doi.org/10.1016/j.nonrwa.2024.104135 doi: 10.1016/j.nonrwa.2024.104135
    [32] T. X. Li, D. Acosta‐Soba, A. Columbu, G. Viglialoro, Dissipative gradient nonlinearities prevent $\delta$-formations in local and nonlocal attraction-repulsion chemotaxis models, Stud. Appl. Math., 154 (2025), e70018. https://doi.org/10.1111/sapm.70018 doi: 10.1111/sapm.70018
    [33] S. Gnanasekaran, A. Columbu, R. D. Fuentes, N. Nithyadevi, Global existence and lower bounds in a class of tumor-immune cell interactions chemotaxis systems, Discrete Cont. Dyn.-S, 18 (2025), 1636–1659. https://doi.org/10.3934/dcdss.2024174 doi: 10.3934/dcdss.2024174
    [34] H. Christopher Frey, S. R. Patil, Identification and review of sensitivity analysis methods, Risk Anal., 22 (2002), 553–578. https://doi.org/10.1111/0272-4332.00039 doi: 10.1111/0272-4332.00039
    [35] S. Sangsawang, U. W. Humphries, A. Khan, P. Pongsumpun, Sensitivity analysis of cassava mosaic disease with saturation incidence rate model, AIMS Mathematics, 8 (2023), 6233–6254. https://doi.org/10.3934/math.2023315 doi: 10.3934/math.2023315
    [36] G. Izzo, Y. Muroya, A. Vecchio, A general discrete time model of population dynamics in the presence of an infection, Discrete Dyn. Nat. Soc., 2009 (2009), 143019. https://doi.org/10.1155/2009/143019 doi: 10.1155/2009/143019
    [37] J. M. Heffernan, R. J. Smith, L. M. Wahl, Perspectives on the basic reproductive ratio, J. R. Soc. Interface, 2 (2005), 281–293. https://doi.org/10.1098/rsif.2005.0042 doi: 10.1098/rsif.2005.0042
    [38] P. Van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
    [39] S. Reja, S. Ghosh, I. Ghosh, A. Paul, S. Bhattacharya, Investigation and control strategy for canine distemper disease on endangered wild dog species: A model-based approach, SN Appl. Sci., 4 (2022), 176. https://doi.org/10.1007/s42452-022-05053-5 doi: 10.1007/s42452-022-05053-5
    [40] M. C. M. De Jong, O. Diekmann, J. A. P. Heesterbeek, The computation of $R_0$ for discrete-time epidemic models with dynamic heterogeneity, Math. Biosci., 119 (1994), 97–114. https://doi.org/10.1016/0025-5564(94)90006-X doi: 10.1016/0025-5564(94)90006-X
    [41] L. J. S. Allen, P. van den Driessche, The basic reproduction number in some discrete-time epidemic models, J. Differ. Equ. Appl., 14 (2008), 1127–1147. https://doi.org/10.1080/10236190802332308 doi: 10.1080/10236190802332308
    [42] K. Ogata, Discrete-time control systems, Prentice-Hall. 1995.
    [43] M. Benidir, On the root distribution of general polynomials with respect to the unit circle, Signal Process., 53 (1996), 75–82. https://doi.org/10.1016/0165-1684(96)00077-1 doi: 10.1016/0165-1684(96)00077-1
    [44] G. L. Wen, Criterion to identify Hopf bifurcations in maps of arbitrary dimension, Phys. Rev. E, 72 (2005), 026201. https://doi.org/10.1103/PhysRevE.72.026201 doi: 10.1103/PhysRevE.72.026201
    [45] U. Saeed, I. Ali, Q. Din, Neimark–Sacker bifurcation and chaos control in discrete-time predator-prey model with parasites, Nonlinear Dyn., 94 (2018), 2527–2536. https://doi.org/10.1007/s11071-018-4507-4 doi: 10.1007/s11071-018-4507-4
    [46] L. Rimbaud, C. Bruchou, S. Dallot, D. R. J. Pleydell, E. Jacquot, S. Soubeyrand, et al., Using sensitivity analysis to identify key factors for the propagation of a plant epidemic, R. Soc. Open Sci., 5 (2018), 171435. https://doi.org/10.1098/rsos.171435 doi: 10.1098/rsos.171435
    [47] J. Y. Wu, R. Dhingra, M. Gambhir, J. V. Remais, Sensitivity analysis of infectious disease models: methods, advances and their application, J. R. Soc. Interface, 10 (2013), 20121018. https://doi.org/10.1098/rsif.2012.1018 doi: 10.1098/rsif.2012.1018
    [48] S. Marino, I. B. Hogue, C. J. Ray, D. E. Kirschner, A methodology for performing global uncertainty and sensitivity analysis in systems biology, J. Theor. Biol., 254 (2008), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 doi: 10.1016/j.jtbi.2008.04.011
    [49] I. Y. M. Sobol, On sensitivity estimation for nonlinear mathematical models, Matematicheskoe Modelirovanie, 2 (1990), 112–118.
    [50] I. M. Sobol, Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Simulat., 55 (2001), 271–280. https://doi.org/10.1016/S0378-4754(00)00270-6 doi: 10.1016/S0378-4754(00)00270-6
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