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Mathematical and computational analysis of a Kayo-Kengne-Akgül fractional-order Lassa fever model

  • Published: 09 July 2026
  • MSC : 34D20, 34K20, 34K60, 92C60, 92D45

  • This study developed a Caputo-type Kayo-Kengne-Akgül (KKA) fractional model for Lassa fever transmission with memory in coupled human-rodent dynamics. The model contains five compartments: susceptible, infected, and recovered humans, together with susceptible and infected rodents. Using the inverse relation between the KKA derivative and its associated integral, the system was rewritten as an equivalent Volterra-type integral equation. The analysis proved positivity, boundedness, existence, uniqueness, and Ulam-Hyers stability. For computation, a two-step KKA Adams-Bashforth scheme was constructed to examine the effect of the fractional order, showing that smaller orders produce stronger memory and slower epidemic evolution. A deep neural network surrogate was trained on the numerical trajectories, and parameter estimation from clean and noisy synthetic data showed close agreement between the reference and recovered solutions for all compartments and selected transmission parameters.

    Citation: Ramsha Shafqat, Mohammed M. Alshamrani. Mathematical and computational analysis of a Kayo-Kengne-Akgül fractional-order Lassa fever model[J]. AIMS Mathematics, 2026, 11(7): 20143-20169. doi: 10.3934/math.2026818

    Related Papers:

  • This study developed a Caputo-type Kayo-Kengne-Akgül (KKA) fractional model for Lassa fever transmission with memory in coupled human-rodent dynamics. The model contains five compartments: susceptible, infected, and recovered humans, together with susceptible and infected rodents. Using the inverse relation between the KKA derivative and its associated integral, the system was rewritten as an equivalent Volterra-type integral equation. The analysis proved positivity, boundedness, existence, uniqueness, and Ulam-Hyers stability. For computation, a two-step KKA Adams-Bashforth scheme was constructed to examine the effect of the fractional order, showing that smaller orders produce stronger memory and slower epidemic evolution. A deep neural network surrogate was trained on the numerical trajectories, and parameter estimation from clean and noisy synthetic data showed close agreement between the reference and recovered solutions for all compartments and selected transmission parameters.



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    [1] K. O. Achema, D. J. Yayaha, W. T. Ademosu, Mathematical model formulation and analysis of the transmission dynamics of Lassa fever, Ann. Commun. Math., 9 (2026), 9. https://doi.org/10.62072/acm.2026.09009 doi: 10.62072/acm.2026.09009
    [2] J. U. A. Grace, I. J. Egoh, N. Udensi, Epidemiological trends of Lassa fever in Nigeria from 2015–2021: A review, Therapeut. Adv. Infect. Dis., 8 (2021), 20499361211058252. https://doi.org/10.1177/20499361211058252 doi: 10.1177/20499361211058252
    [3] A. Musa, K. Osuolale, D. Lawal, A. Salako, F. Aponinuola, W. Tijani, et al., Modelling seasonal variation and Lassa fever outbreak in Nigeria: A predictive approach, Int. J. Data Sci. Anal., 10 (2024), 100–108. https://doi.org/10.11648/j.ijdsa.20241005.12 doi: 10.11648/j.ijdsa.20241005.12
    [4] E. A. Bakare, E. B. Are, O. E. Abolarin, S. A. Osanyinlusi, B. Ngwu, O. N. Ubaka, Mathematical modelling and analysis of transmission dynamics of Lassa fever, J. Appl. Math., 2020 (2020), 6131708. https://doi.org/10.1155/2020/6131708 doi: 10.1155/2020/6131708
    [5] I. O. Abiola, A. S. Oyewole, T. T. Yusuf, Mathematical modelling of Lassa-fever transmission dynamics with optimal control of selected control measures, Model. Earth Syst. Environ., 10 (2024), 7443–7458. https://doi.org/10.1007/s40808-024-02168-z doi: 10.1007/s40808-024-02168-z
    [6] S. S. Musa, S. Zhao, D. Gao, Q. Lin, G. Chowell, D. He, Mechanistic modelling of the large-scale Lassa fever epidemics in Nigeria from 2016 to 2019, J. Theor. Biol., 493 (2020), 110209. https://doi.org/10.1016/j.jtbi.2020.110209 doi: 10.1016/j.jtbi.2020.110209
    [7] A. A. Ayoade, O. Aliu, O. Taiye, The effect of treatment compliance on the dynamics and control of Lassa fever: An insight from mathematical modeling, SeMA J., 82 (2025), 89–108. https://doi.org/10.1007/s40324-024-00353-9 doi: 10.1007/s40324-024-00353-9
    [8] S. Dachollom, C. E. Madubueze, Mathematical model of the transmission dynamics of Lassa fever infection with controls, Math. Model. Appl., 5 (2020), 65–86. https://doi.org/10.11648/j.mma.20200502.13 doi: 10.11648/j.mma.20200502.13
    [9] A. El-Mesady, T. M. Al-shami, H. M. Ali, Optimal control efforts to reduce the transmission of HPV in a fractional-order mathematical model, Boundary Value Probl., 2025 (2025), 42. https://doi.org/10.1186/s13661-024-01991-8 doi: 10.1186/s13661-024-01991-8
    [10] A. Elsonbaty, T. M. Al-Shami, A. El-Mesady, Unveiling the dynamics of meningitis infections: A comprehensive study of a novel fractional-order model with optimal control strategies, Boundary Value Probl., 2025 (2025), 48. https://doi.org/10.1186/s13661-025-02034-6 doi: 10.1186/s13661-025-02034-6
    [11] R. Shafqat, M. M. Alshamrani, Deep learning for parameter estimation in a typhoid fever model, AIMS Math., 11 (2026), 14984–15007. https://doi.org/10.3934/math.2026616 doi: 10.3934/math.2026616
    [12] R. Shafqat, A. Alsaadi, A hybrid predictive framework for Zika dynamics using the normalized Caputo-Fabrizio operator, J. Math., 2026 (2026), 4681248. https://doi.org/10.1155/jom/4681248 doi: 10.1155/jom/4681248
    [13] A. Al-Quran, R. Shafqat, A. Alsaadi, A. M. Djaouti, Well-posedness and Ulam-Hyers stability of a normalized Caputo-Fabrizio fractional model for ischemic heart disease progression, J. Math., 2026 (2026), 9509503. https://doi.org/10.1155/jom/9509503 doi: 10.1155/jom/9509503
    [14] R. Shafqat, A. Al-Quran, A. Alsaadi, A. M. Djaouti, Normalized Caputo-Fabrizio SVIR modeling and bifurcation analysis, Sci. Rep., 1, (2026), 8193. https://doi.org/10.1038/s41598-026-38301-4 doi: 10.1038/s41598-026-38301-4
    [15] D. Kayo, A. Akgül, Adams-Bashforth scheme and Kayo-Kengne-Akgül derivative: Connexion and chaotic modelling, Univ. J. Math. Appl., 9 (2026), 53–63. https://doi.org/10.32323/ujma.1879909 doi: 10.32323/ujma.1879909
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