Is reinfection negligible effect in COVID-19? A mathematical study on the effects of reinfection in COVID-19

被引:4
作者
Tamilalagan, P. [1 ]
Krithika, B. [1 ]
Manivannan, P. [2 ]
Karthiga, S. [3 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Sch Phys Sci, Dept Math, Coimbatore, India
[2] Mepco Schlenk Engn Coll, Dept Math, Virudunagar, India
[3] Affiliated Bharathidasan Univ, Seethalakshmi Ramaswami Coll, PG & Res Dept Phys, Trichy, India
关键词
COVID-19; fractional order dynamical systems; mathematical model; reinfection; stability analysis; transmission dynamics; CORONAVIRUS DISEASE; EPIDEMIC; MODELS;
D O I
10.1002/mma.9614
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Serological studies show that besides the development of suitable antibodies that are evidenced in people who get infected with SARS-CoV2 or in people who are vaccinated, the possibility of getting reinfected with SARS-CoV2 remains non-zero (may be finite). The present article studies how far this possibility of reinfection impacts the transmission dynamics of COVID-19. Considering a six compartment mathematical model, we have studied the transmission dynamics of the disease and presented the situations that will lead to endemic-free (also endemic) state. Considering the COVID-19 waves in India during the spread of SARS-CoV-2, delta variant of SARS-CoV-2, and Omicron variant, the parameters of the model are estimated corresponding to these three situations. As expected, the obtained parameters lie in the stable region of endemic state. The changes in dynamics of the system with the reinfection is studied, and it shows that its effects are not neglible. Even finite value of reinfection can significantly vary the number of infected individuals, and it could explain secondary (smaller) rise in the COVID-19 cases after the COVID-19 wave. We also study the dynamics of the system through fractional order differential equations.
引用
收藏
页码:19115 / 19134
页数:20
相关论文
共 45 条
  • [1] Stability and bifurcation analysis of a fractional-order model of cell-to-cell spread of HIV-1 with a discrete time delay
    Abbas, Syed
    Tyagi, Swati
    Kumar, Pushpendra
    Erturk, Vedat Suat
    Momani, Shaher
    [J]. MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2022, 45 (11) : 7081 - 7095
  • [2] Mathematical analysis of COVID-19 via new mathematical model
    Abdullah
    Ahmad, Saeed
    Owyed, Saud
    Abdel-Aty, Abdel-Haleem
    Mahmoud, Emad E.
    Shah, Kamal
    Alrabaiah, Hussam
    [J]. CHAOS SOLITONS & FRACTALS, 2021, 143
  • [3] Andrew M. M., 2020, JMIR PUBLIC HLTH SUR, V6
  • [4] [Anonymous], 2020, SER SURV WHO COVID19
  • [5] [Anonymous], 2020, AV LIF EXP IND
  • [6] Bandyopadhyay B, 2015, LECT NOTES ELECTR EN, V317, P1, DOI 10.1007/978-3-319-08621-7
  • [7] Outbreak caused by the SARS-CoV-2 Omicron variant in Norway, November to December 2021
    Brandal, Lin T.
    MacDonald, Emily
    Veneti, Lamprini
    Ravlo, Tine
    Lange, Heidi
    Naseer, Umaer
    Feruglio, Siri
    Bragstad, Karoline
    Hungnes, Olav
    Odeskaug, Liz E.
    Hagen, Frode
    Hanch-Hansen, Kristian E.
    Lind, Andreas
    Watle, Sara Viksmoen
    Taxt, Arne M.
    Johansen, Mia
    Vold, Line
    Aavitsland, Preben
    Nygard, Karin
    Madslien, Elisabeth H.
    [J]. EUROSURVEILLANCE, 2021, 26 (50)
  • [8] A multiregional extension of the SIR model, with application to the COVID-19 spread in Italy
    Brugnano, Luigi
    Iavernaro, Felice
    Zanzottera, Paolo
    [J]. MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2021, 44 (06) : 4414 - 4427
  • [9] A Simulation of a COVID-19 Epidemic Based on a Deterministic SEIR Model
    Carcione, Jose M.
    Santos, Juan E.
    Bagaini, Claudio
    Ba, Jing
    [J]. FRONTIERS IN PUBLIC HEALTH, 2020, 8
  • [10] Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model
    Chitnis, Nakul
    Hyman, James M.
    Cushing, Jim M.
    [J]. BULLETIN OF MATHEMATICAL BIOLOGY, 2008, 70 (05) : 1272 - 1296