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Mathematical modeling, analysis and numerical simulation of the COVID-19 transmission with mitigation of control strategies used in Cameroon

Author

Listed:
  • Djaoue, Seraphin
  • Guilsou Kolaye, Gabriel
  • Abboubakar, Hamadjam
  • Abba Ari, Ado Adamou
  • Damakoa, Irepran

Abstract

In this paper, we formulated a general model of COVID-19model transmission using biological features of the disease and control strategies based on the isolation of exposed people, confinement (lock-downs) of the human population, testing people living risks area, wearing of masks and respect of hygienic rules. We provide a theoretical study of the model. We derive the basic reproduction number R0which determines the extinction and the persistence of the infection. It is shown that the model exhibits a backward bifurcation at R0=1. The sensitivity analysis of the model has been performed to determine the impact of related parameters on outbreak severity. It is observed that the asymptomatic infectious group of individuals may play a major role in the spreading of transmission. Moreover, various mitigation strategies are investigated using the proposed model. A numerical evaluation of control strategies has been performed. We found that isolation has a real impact on COVID-19transmission. When efforts are made through the tracing to isolate 80% of exposed people the disease disappears about 100 days. Although partial confinement does not eradicate the disease it is observed that, during partial confinement, when at least 10% of the partially confined population is totally confined, COVID-19 spread stops after 150 days. The strategy of massif testing has also a real impact on the disease. In that model, we found that when more than 95% of moderate and symptomatic infected people are identified and isolated, the disease is also really controlled after 90 days. The wearing of masks and respecting hygiene rules are fundamental conditions to control the COVID-19.

Suggested Citation

  • Djaoue, Seraphin & Guilsou Kolaye, Gabriel & Abboubakar, Hamadjam & Abba Ari, Ado Adamou & Damakoa, Irepran, 2020. "Mathematical modeling, analysis and numerical simulation of the COVID-19 transmission with mitigation of control strategies used in Cameroon," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:chsofr:v:139:y:2020:i:c:s0960077920306779
    DOI: 10.1016/j.chaos.2020.110281
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    References listed on IDEAS

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    1. Aliyu, Aliyu Isa & Inc, Mustafa & Yusuf, Abdullahi & Baleanu, Dumitru, 2018. "A fractional model of vertical transmission and cure of vector-borne diseases pertaining to the Atangana–Baleanu fractional derivatives," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 268-277.
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    4. Kassa, Semu M. & Njagarah, John B.H. & Terefe, Yibeltal A., 2020. "Analysis of the mitigation strategies for COVID-19: From mathematical modelling perspective," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    5. Qureshi, Sania & Atangana, Abdon, 2019. "Mathematical analysis of dengue fever outbreak by novel fractional operators with field data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
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    Cited by:

    1. Zhongxiang Chen & Zhiquan Shu & Xiuxiang Huang & Ke Peng & Jiaji Pan, 2021. "Modelling Analysis of COVID-19 Transmission and the State of Emergency in Japan," IJERPH, MDPI, vol. 18(13), pages 1-15, June.
    2. Abboubakar, Hamadjam & Kouchéré Guidzavaï, Albert & Yangla, Joseph & Damakoa, Irépran & Mouangue, Ruben, 2021. "Mathematical modeling and projections of a vector-borne disease with optimal control strategies: A case study of the Chikungunya in Chad," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Yu, Zhenhua & Zhang, Jingmeng & Zhang, Yun & Cong, Xuya & Li, Xiaobo & Mostafa, Almetwally M., 2024. "Mathematical modeling and simulation for COVID-19 with mutant and quarantined strategy," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    4. Paul, James Nicodemus & Mbalawata, Isambi Sailon & Mirau, Silas Steven & Masandawa, Lemjini, 2023. "Mathematical modeling of vaccination as a control measure of stress to fight COVID-19 infections," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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