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Mathematical analysis of spread and control of the novel corona virus (COVID-19) in China

Author

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  • Din, Anwarud
  • Li, Yongjin
  • Khan, Tahir
  • Zaman, Gul

Abstract

Number of well-known contagious diseases exist around the world that mainly include HIV, Hepatitis B, influenzas etc., among these, a recently contested coronavirus (COVID-19) is a serious class of such transmissible syndromes. Abundant scientific evidence the wild animals are believed to be the primary hosts of the virus. Majority of such cases are considered to be human-to-human transmission, while a few are due to wild animals-to-human transmission and substantial burdens on healthcare system following this spread. To understand the dynamical behavior such diseases, we fitted a susceptible-infectious-quarantined model for human cases with constant proportions. We proposed a model that provide better constraints on understanding the climaxes of such unseen disastrous spread, relevant consequences, and suggesting future imperative strategies need to be adopted. The main features of the work include the positivity, boundedness, existence and uniqueness of solution of the model. The conditions were derived under which the COVID-19 may extinct or persist in the population. Sensitivity and estimation of those important parameters have been carried out that plays key role in the transmission mechanism. To optimize the spread of such disease, we present a control problem for further analysis using two control measures. The necessary conditions have been derived using the Pontryagin’s maximum principle. Parameter values have been estimated from the real data and experimental numerical simulations are presented for comparison as well as verification of theoretical results. The obtained numerical results also present the verification, accuracy, validation, and robustness of the proposed scheme.

Suggested Citation

  • Din, Anwarud & Li, Yongjin & Khan, Tahir & Zaman, Gul, 2020. "Mathematical analysis of spread and control of the novel corona virus (COVID-19) in China," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920306822
    DOI: 10.1016/j.chaos.2020.110286
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    References listed on IDEAS

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    1. McIntosh, Emma & Clarke, Philip & Frew, Emma & Louviere, Jordan (ed.), 2010. "Applied Methods of Cost-Benefit Analysis in Health Care," OUP Catalogue, Oxford University Press, number 9780199237128, Decembrie.
    2. Atangana, Abdon, 2020. "Modelling the spread of COVID-19 with new fractal-fractional operators: Can the lockdown save mankind before vaccination?," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    3. Khan, Tahir & Ullah, Zakir & Ali, Nigar & Zaman, Gul, 2019. "Modeling and control of the hepatitis B virus spreading using an epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 124(C), pages 1-9.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Zhang, Ge & Li, Zhiming & Din, Anwarud, 2022. "A stochastic SIQR epidemic model with Lévy jumps and three-time delays," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    2. Wen Dong & Peng Zhang & Quan-Li Xu & Zhong-Da Ren & Jie Wang, 2022. "A Study on a Neural Network Risk Simulation Model Construction for Avian Influenza A (H7N9) Outbreaks in Humans in China during 2013–2017," IJERPH, MDPI, vol. 19(17), pages 1-16, August.
    3. Rahman, Mati ur & Ahmad, Saeed & Matoog, R.T. & Alshehri, Nawal A. & Khan, Tahir, 2021. "Study on the mathematical modelling of COVID-19 with Caputo-Fabrizio operator," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    4. Yehuda Arav & Eyal Fattal & Ziv Klausner, 2022. "Is the Increased Transmissibility of SARS-CoV-2 Variants Driven by within or Outside-Host Processes?," Mathematics, MDPI, vol. 10(19), pages 1-17, September.
    5. Din, Anwarud & Li, Yongjin & Yusuf, Abdullahi, 2021. "Delayed hepatitis B epidemic model with stochastic analysis," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    6. Yassine Sabbar & Asad Khan & Anwarud Din, 2022. "Probabilistic Analysis of a Marine Ecological System with Intense Variability," Mathematics, MDPI, vol. 10(13), pages 1-19, June.
    7. Xuan Leng & Asad Khan & Anwarud Din, 2023. "Probability Analysis of a Stochastic Non-Autonomous SIQRC Model with Inference," Mathematics, MDPI, vol. 11(8), pages 1-18, April.
    8. Ihtisham Ul Haq & Numan Ullah & Nigar Ali & Kottakkaran Sooppy Nisar, 2022. "A New Mathematical Model of COVID-19 with Quarantine and Vaccination," Mathematics, MDPI, vol. 11(1), pages 1-21, December.

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