Year 2024,
Volume: 4 Issue: 3, 296 - 334, 30.09.2024
Isaac Kwasi Adu
,
Fredrick Asenso Wireko
,
Samuel Akwasi Adarkwa
,
Gerald Ohene Agyekum
References
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- [4] Savini, H., Janvier, F., Karkowski, L., Billhot, M., Aletti, M., Bordes, J. et al. Occupational exposures to Ebola virus in Ebola treatment center, Conakry, Guinea. Emerging Infectious Diseases, 23(8), 1380-1383, (2017).
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Mathematical analysis of Ebola considering transmission at treatment centres and survivor relapse using fractal-fractional Caputo derivatives in Uganda
Year 2024,
Volume: 4 Issue: 3, 296 - 334, 30.09.2024
Isaac Kwasi Adu
,
Fredrick Asenso Wireko
,
Samuel Akwasi Adarkwa
,
Gerald Ohene Agyekum
Abstract
In this article, we seek to formulate a robust mathematical model to study the Ebola disease through fractal-fractional operators. The study thus incorporates the transmission rate in the treatment centers and the relapse rate, since the Ebola virus persists or mostly hides in the immunologically protected sites of survivors. The Ebola virus disease (EVD) is one of the infectious diseases that has recorded a high death rate in countries where it is endemic, and Uganda is not an exception. The world at large has suffered from this deadly disease since 1976 when it was declared epidemic by the World Health Organization. The study employed fractal-fractional operators to identify the epidemiological patterns of EVD, especially in treatment centers and relapse. Memory loss and relapse are mostly observed in EVD survivors and this justifies the use of fractional operators to capture the true dynamics of the disease. Through dynamical analysis, the model is proven to be positive and bounded in the region. The model is further explicitly shown to have a solution that is unique and stable. The reproduction number was duly computed by using the next-generation matrix approach. By taking EVD epidemic cases in Uganda, the study fitted all parameters to real data. It has been shown through sensitivity index analysis that the transmission rate outside treatment centers and relapse have a significant effect on the endemic state of the disease, as they lead to an increase in the basic reproduction ratio.
References
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- [2] Adu, I.K., Wireko, F.A., Osman, M.A.L. and Asamoah, J.K.K. A fractional order Ebola transmission model for dogs and humans. Scientific African, 24, e02230, (2024).
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- [4] Savini, H., Janvier, F., Karkowski, L., Billhot, M., Aletti, M., Bordes, J. et al. Occupational exposures to Ebola virus in Ebola treatment center, Conakry, Guinea. Emerging Infectious Diseases, 23(8), 1380-1383, (2017).
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- [7] Adu, I.K., Wireko, F.A., Sebil, C. and Asamoah, J.K.K. A fractal-fractional model of Ebola with reinfection. Results in Physics, 52, 106893, (2023).
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- [21] Arik, I.A., Sari, H.K. and Araz, S.˙I. Numerical simulation of Covid-19 model with integer and non-integer order: The effect of environment and social distancing. Results in Physics, 51, 106725, (2023).
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- [23] Rafiq, M., Ahmad, W., Abbas, M. and Baleanu, D. A reliable and competitive mathematical analysis of Ebola epidemic model. Advances in Difference Equations, 2020, 540, (2020).
- [24] Nazir, A., Ahmed, N., Khan, U., Mohyud-Din, S.T., Nisar, K.S. and Khan, I. An advanced version of a conformable mathematical model of Ebola virus disease in Africa. Alexandria Engineering Journal, 59(5), 3261-3268, (2020).
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- [26] Singh, H. Analysis for fractional dynamics of Ebola virus model. Chaos, Solitons & Fractals, 138, 109992, (2020).
- [27] Farman, M., Akgül, A., Abdeljawad, T., Naik, P.A., Bukhari, N. and Ahmad, A. Modeling and analysis of fractional order Ebola virus model with Mittag-Leffler kernel. Alexandria Engineering Journal,, 61(3), 2062-2073, (2022).
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- [29] Addai, E., Zhang, L., Preko, A.K. and Asamoah, J.K.K. Fractional order epidemiological model of SARS-CoV-2 dynamism involving Alzheimer’s disease. Healthcare Analytics, 2, 100114, (2022).
- [30] Qureshi, A.I., Chughtai, M., Loua, T.O., Pe Kolie, J., Camara, H.F.S., Ishfaq, M.F. et al. Study of Ebola virus disease survivors in Guinea. Clinical Infectious Diseases, 61(7), 1035-1042, (2015).
- [31] Kengne, J.N. and Tadmon, C. Ebola virus disease model with a nonlinear incidence rate and density-dependent treatment. Infectious Disease Modelling, 9(3), 775-804, (2024).
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- [33] Rezapour, S., Asamoah, J.K.K., Hussain, A., Ahmad, H., Banerjee, R., Etemad, S. and Botmart, T. A theoretical and numerical analysis of a fractal-fractional two-strain model of meningitis. Results in Physics, 39, 105775, (2022).
- [34] Atangana, A. Fractal-fractional differentiation and integration: connecting fractal calculus and fractional calculus to predict complex system. Chaos, Solitons & Fractals, 102, 396-406, (2017).
- [35] Samet, B., Vetro, C. and Vetro, P. Fixed point theorems for α-ψ-contractive type mappings. Nonlinear Analysis: Theory, Methods & Applications, 75(4), 2154-2165, (2012).
- [36] Jiang, S., Zhang, J., Zhang, Q. and Zhang, Z. Fast evaluation of the Caputo fractional derivative and its applications to fractional diffusion equations. Communications in Computational Physics, 21(3), 650-678, (2017).
- [37] Padder, A., Almutairi, L., Qureshi, S., Soomro, A., Afroz, A., Hincal, E. and Tassaddiq, A. Dynamical analysis of generalized tumor model with Caputo fractional-order derivative. Fractal and Fractional, 7(3), 258, (2023).
- [38] Sikora, B. Remarks on the Caputo fractional derivative. Minut, 5, 76-84, (2023).
- [39] Baba, I.A., Ahmed, I., Al-Mdallal, Q. M., Jarad, F. and Yunusa, S. Numerical and theoretical analysis of an awareness COVID-19 epidemic model via generalized Atangana-Baleanu fractional derivative. Journal of Applied Mathematics and Computational Mechanics, 21(1), 7-18, (2022).
- [40] Ahmed, I., Yusuf, A., Ibrahim, A., Kumam, P. and Ibrahim, M.J. A mathematical model of the ongoing coronavirus disease (COVID-19) pandemic: a case study in Turkey. Science & Technology Asia, 27(4), 248-258, (2022).
- [41] Hussain, A., Ahmed, I., Yusuf, A. and Ibrahim, M.J. Existence and stability analysis of a fractional-order COVID-19 model. Bangmod International Journal of Mathematical and Computational Science, 7, 102-125, (2021).
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- [46] Gopal, K., Lee, L.S. and Seow, H.V. Parameter estimation of compartmental epidemiological model using harmony search algorithm and its variants. Applied Sciences, 11(3), 1138, (2021).
- [47] Asamoah, J.K.K., Owusu, M.A., Jin, Z., Oduro, F.T., Abidemi, A. and Gyasi, E.O. Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment: using data from Ghana. Chaos, Solitons & Fractals, 140, 110103, (2020).
- [48] Asamoah, J.K.K., Jin, Z., Sun, G.Q., Seidu, B., Yankson, E., Abidemi, A. et al. Sensitivity assessment and optimal economic evaluation of a new COVID-19 compartmental epidemic model with control interventions. Chaos, Solitons & Fractals, 146, 110885, (2021).
- [49] Allahamou, A., Azroul, E., Hammouch, Z. and Alaoui, A.L. Modeling and numerical investigation of a conformable co-infection model for describing Hantavirus of the European moles. Mathematical Methods in the Applied Sciences, 45(5), 2736-2759, (2022).
- [50] Hamou, A.A., Rasul, R.R.Q., Hammouch, Z. and Özdemir, N. Analysis and dynamics of a mathematical model to predict unreported cases of COVID-19 epidemic in Morocco. Computational and Applied Mathematics, 41, 289, (2022).
- [51] Alla Hamou, A., Azroul, E. and Lamrani Alaoui, A. Fractional model and numerical algorithms for predicting COVID-19 with isolation and quarantine strategies. International Journal of Applied and Computational Mathematics, Springer, 7, 142, (2021).
- [52] Hamou, A.A., Azroul, E., Hammouch, Z. and Alaoui, A.L. A fractional multi-order model to predict the COVID-19 outbreak in Morocco. Applied and Computational Mathematics, 20(1), 177-203, (2020).
- [53] Martcheva, M. An Introduction to Mathematical Epidemiology (Vol. 61). Springer: New York, (2015).
- [54] Asamoah, J.K.K. A fractional mathematical model of heartwater transmission dynamics considering nymph and adult amblyomma ticks. Chaos, Solitons & Fractals, 174, 113905, (2023).
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