IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v149y2021ics0960077921004057.html
   My bibliography  Save this article

Nonlinear control of infection spread based on a deterministic SEIR model

Author

Listed:
  • Piccirillo, Vinicius

Abstract

In this study, a mathematical model (SEIR model) with a restriction parameter is used to explore the dynamic of the COVID-19 pandemic. This work presents a nonlinear and robust control algorithm based on variable structure control (VSC) to control the transmission of coronavirus disease (COVID-19). The VSC algorithm is a control gain switching technique in which is necessary to define a switching surface. Three switching surfaces are proposed based on rules that depend on: (i) exposed and infected population, (ii) susceptible and infected population, and (iii) susceptible and total population. In case (iii) a model-based state estimator is presented based on the extended Kalman filter (EKF) and the estimator is used in combination with the VSC. Numerical results demonstrate that the proposed control strategies have the ability to flatten the infection curve. In addition, the simulations show that the success of lowering and flattening the epidemic peak is strongly dependent on the chosen switching surfaces. A comparison between the VSC and sliding mode control (SMC) is presented showing that the VSC control can provide better performance taking into account two aspects: time duration of pandemic and the flattened curve peak with respect to SMC.

Suggested Citation

  • Piccirillo, Vinicius, 2021. "Nonlinear control of infection spread based on a deterministic SEIR model," Chaos, Solitons & Fractals, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:chsofr:v:149:y:2021:i:c:s0960077921004057
    DOI: 10.1016/j.chaos.2021.111051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921004057
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.111051?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Ndaïrou, Faïçal & Area, Iván & Nieto, Juan J. & Silva, Cristiana J. & Torres, Delfim F.M., 2021. "Fractional model of COVID-19 applied to Galicia, Spain and Portugal," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shami, Labib & Lazebnik, Teddy, 2022. "Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    2. Yuan, Yiran & Li, Ning, 2022. "Optimal control and cost-effectiveness analysis for a COVID-19 model with individual protection awareness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    3. Lazebnik, Teddy, 2023. "Computational applications of extended SIR models: A review focused on airborne pandemics," Ecological Modelling, Elsevier, vol. 483(C).
    4. Shirazian, Mohammad, 2023. "A new acceleration of variational iteration method for initial value problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 214(C), pages 246-259.
    5. Gabrick, Enrique C. & Protachevicz, Paulo R. & Batista, Antonio M. & Iarosz, Kelly C. & de Souza, Silvio L.T. & Almeida, Alexandre C.L. & Szezech, José D. & Mugnaine, Michele & Caldas, Iberê L., 2022. "Effect of two vaccine doses in the SEIR epidemic model using a stochastic cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed M. Mousa & Fahad Alsharari, 2021. "A Comparative Numerical Study and Stability Analysis for a Fractional-Order SIR Model of Childhood Diseases," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    2. Pau Fonseca i Casas & Joan Garcia i Subirana & Víctor García i Carrasco & Xavier Pi i Palomés, 2021. "SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    3. Samad Noeiaghdam & Sanda Micula & Juan J. Nieto, 2021. "A Novel Technique to Control the Accuracy of a Nonlinear Fractional Order Model of COVID-19: Application of the CESTAC Method and the CADNA Library," Mathematics, MDPI, vol. 9(12), pages 1-26, June.
    4. Iloanusi, Ogechukwu & Ross, Arun, 2021. "Leveraging weather data for forecasting cases-to-mortality rates due to COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Rubayyi T. Alqahtani & Abdelhamid Ajbar, 2021. "Study of Dynamics of a COVID-19 Model for Saudi Arabia with Vaccination Rate, Saturated Treatment Function and Saturated Incidence Rate," Mathematics, MDPI, vol. 9(23), pages 1-13, December.
    6. Baba, Isa Abdullahi & Rihan, Fathalla A., 2022. "A fractional–order model with different strains of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    7. Zhu, Cheng-Cheng & Zhu, Jiang, 2021. "Dynamic analysis of a delayed COVID-19 epidemic with home quarantine in temporal-spatial heterogeneous via global exponential attractor method," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    8. Borah, Manashita & Das, Debanita & Gayan, Antara & Fenton, Flavio & Cherry, Elizabeth, 2021. "Control and anticontrol of chaos in fractional-order models of Diabetes, HIV, Dengue, Migraine, Parkinson's and Ebola virus diseases," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:149:y:2021:i:c:s0960077921004057. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.