Essential Analysis of New SEVIR Model: A Five Case Epidemic Model

In this work, we introduce a new SEVIR epidemic model to analyze the dynamics of infectious diseases by incorporating the key compartments such as susceptible, exposed, vaccinated, infected, and recovered populations. We add the vaccination compartment in the current model and calculate the consequences concerning the disease spreading; it is significantly relevant at the present day considering the general policies of worldwide vaccinations. For a stringent assessment of stability, it should involve derivation of a basic reproduction number, as this parameter characterizes whether an infection will be spread at all. Our results demonstrate that when we have R0 < 1, the disease-free equilibrium is locally asymptotically stable, which implies that an infection will eventually die out. We also identify two distinguished disease-dependent equilibrium points for the first time, giving much deeper insight into long term behavior of the disease. Numerical simulations show the efficacy of vaccination toward reducing the newly infected individuals and suggest the model can predict stabilization for all compartments over time. The exposed and recovered population increases and stabilizes as the susceptible, infected, and vaccinated populations decline. In this regard, these are valuable insights into the progression of epidemics and put emphasis on vaccination programs. Our model provides a perspective on disease control by taking into account the interplay between vaccination and infection dynamics. It can be very useful for predicting future outbreaks and can guide public health policy. Future work will extend the model by adding quarantine measures to further hone our understanding of disease transmission.

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Publication Details

Journal
Contemporary Mathematics
Published
2024-12-03
DOI
https://doi.org/10.37256/cm.5420245746
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Essential Analysis of New SEVIR Model: A Five Case Epidemic Model

R. Udhayakumar, Prasantha Bharathi Dhandapani, Kalpana Umapathy, Balaganesan Palanivelu
1 links
Contemporary Mathematics
COVID-19 epidemiological studies
article

Essential Analysis of New SEVIR Model: A Five Case Epidemic Model

R. Udhayakumar, Prasantha Bharathi Dhandapani, Kalpana Umapathy, Balaganesan Palanivelu
article en

Abstract

In this work, we introduce a new SEVIR epidemic model to analyze the dynamics of infectious diseases by incorporating the key compartments such as susceptible, exposed, vaccinated, infected, and recovered populations. We add the vaccination compartment in the current model and calculate the consequences concerning the disease spreading; it is significantly relevant at the present day considering the general policies of worldwide vaccinations. For a stringent assessment of stability, it should involve derivation of a basic reproduction number, as this parameter characterizes whether an infection will be spread at all. Our results demonstrate that when we have R0 < 1, the disease-free equilibrium is locally asymptotically stable, which implies that an infection will eventually die out. We also identify two distinguished disease-dependent equilibrium points for the first time, giving much deeper insight into long term behavior of the disease. Numerical simulations show the efficacy of vaccination toward reducing the newly infected individuals and suggest the model can predict stabilization for all compartments over time. The exposed and recovered population increases and stabilizes as the susceptible, infected, and vaccinated populations decline. In this regard, these are valuable insights into the progression of epidemics and put emphasis on vaccination programs. Our model provides a perspective on disease control by taking into account the interplay between vaccination and infection dynamics. It can be very useful for predicting future outbreaks and can guide public health policy. Future work will extend the model by adding quarantine measures to further hone our understanding of disease transmission.

Contemporary Mathematics
AMET University (IN), Sri Eshwar College of Engineering, Vellore Institute of Technology University (IN)
Good health and well-being
Openalex Percentile: Top 76%
COVID-19 epidemiological studies
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