Modeling the Transmission Dynamics of the Ebola Virus: Effects of Quarantine and Vaccination

Authors

  • Wahidullah Zgham South Asian University, Faculty of Mathematics and Computer Science, New Delhi, India
  • Sarojkumar Sahani South Asian University, Faculty of Mathematics and Computer Science, New Delhi, India
  • Hezbullah Rahimi Kabul University, Faculty of Mathematics, Afghanistan

DOI:

https://doi.org/10.62810/jnsr.v2i3.88

Keywords:

Backward Bifurcation, Vaccination Strategies, Ebola Epidemic Dynamics, Mathematical Modeling, Quarantine Implementation, Stability Analysis

Abstract

Quarantine and vaccination of individuals suspected of exposure to infectious agents are fundamental public health strategies that have historically been employed to mitigate the transmission of contagious diseases within human populations. This study introduced a modified SEIVQRD deterministic model to evaluate the population-level effects of quarantine and vaccination on individuals potentially exposed to the Ebola virus. The study showed that the Model exhibits backward bifurcation when . This implies that even when the reproductive number  An unstable endemic and a stable disease-free equilibrium can coexist in less than one. This phenomenon arises from imperfect quarantine and indicates that while  is necessary for adequate infection control; it is no longer sufficient and creates additional challenges for effectively controlling Ebola. Furthermore, the sensitivity analysis revealed that the quarantine effectiveness parameter and the parameter related to the isolation of vulnerable individuals had less influence on the incidence of new Ebola cases. However, vaccinating non-quarantined susceptible individuals significantly affects the infection burden and can lower the reproductive value to less than one. Overall, the Model emphasizes the critical role of vaccination in reducing Ebola virus transmission. Although quarantine measures alone may not be sufficient, their combination with vaccination can significantly reduce infection rates.

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Published

2024-09-30

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