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Global stability analysis of two strains epidemic model with imperfect vaccination and immunity waning in a complex network

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  • Wu, Yucui
  • Zhang, Zhipeng
  • Song, Limei
  • Xia, Chengyi

Abstract

For some epidemic diseases, there exist several strains of the pathogen, which can pose a challenge in controlling the disease and result in complicated dynamics, such as dengue fever and HIV. However, we lack the deep understanding of the dynamic features of interacting multiple strains. In order to reduce the final size of infections and achieve the herd immunity, vaccination is the most effective way of controlling an outbreak. To this end, we put forward the two-strain epidemic model in which vaccination is not perfect and immunity wanes in a complex network. It can be revealed that the disease free equilibrium point of two strains is global asymptotically stable when max{R1,R1}<1, but the coexistence equilibrium point remains and is stable when min{R1,R1}>1. Then, to verify the global stability of each strain dominance equilibrium point, the critical values are further derived. Finally, numerical simulations have been performed to visualize the results of the theoretical analysis. The current results are beneficial to comprehending the dynamics behaviors of multi-strain epidemics.

Suggested Citation

  • Wu, Yucui & Zhang, Zhipeng & Song, Limei & Xia, Chengyi, 2024. "Global stability analysis of two strains epidemic model with imperfect vaccination and immunity waning in a complex network," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:chsofr:v:179:y:2024:i:c:s0960077923013164
    DOI: 10.1016/j.chaos.2023.114414
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    1. Bai, Yanping & Jin, Zhen, 2005. "Prediction of SARS epidemic by BP neural networks with online prediction strategy," Chaos, Solitons & Fractals, Elsevier, vol. 26(2), pages 559-569.
    2. Sharov, Konstantin S., 2020. "Creating and applying SIR modified compartmental model for calculation of COVID-19 lockdown efficiency," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    3. Khan, Asaf & Zaman, Gul, 2018. "Global analysis of an age-structured SEIR endemic model," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 154-165.
    4. Cadoni, Mariano, 2020. "How to reduce epidemic peaks keeping under control the time-span of the epidemic," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    5. Miguel Fudolig & Reka Howard, 2020. "The local stability of a modified multi-strain SIR model for emerging viral strains," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-27, December.
    6. Wang, Yi & Jin, Zhen, 2013. "Global analysis of multiple routes of disease transmission on heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 3869-3880.
    7. Vargas-De-León, Cruz, 2011. "On the global stability of SIS, SIR and SIRS epidemic models with standard incidence," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1106-1110.
    8. Bobryk, R.V., 2021. "Stability analysis of a SIR epidemic model with random parametric perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    9. Baba, Isa Abdullahi & Kaymakamzade, Bilgen & Hincal, Evren, 2018. "Two-strain epidemic model with two vaccinations," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 342-348.
    Full references (including those not matched with items on IDEAS)

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