Analysis of quarantine and liberate effects on viral infection using SEIR and Caputo $ \alpha $-fractional-order model

Document Type : Research Paper

Authors

School of Mathematics and Computer Science, Iran University of Science and Technology, Narmak, Tehran, 1684613114, Iran.

Abstract

Of the various control measures available, lockdown is widely considered to be the most reliable method for containing the spread of Coronavirus. This study presents two mathematical models utilizing $\alpha$-fractional derivatives to investigate the significance of lockdown in reducing the spread of the virus. In this article, the entire population is divided into four groups:
\begin{enumerate}
    \item    The first group comprises the susceptible population who are not under lockdown.
    \item    The second group consists of susceptible individuals who are under lockdown.
    \item The third group comprises infected individuals who are not under lockdown.
    \item    The fourth group consists of infective individuals who are under lockdown.
    \end{enumerate}
One of the aforementioned methods examines the dynamics of COVID-19 by generalizing the SEIR model using $\alpha$-fractional derivatives. The second model comprises five nonlinear differential equations of $\boldsymbol{\alpha}$-fractional order. In both methods, $ \boldsymbol{\alpha} = (\alpha_1,\cdots,\alpha_n) $, where $ 0 < \alpha_i \leq 1 $ for all $ 1 \leq i \leq n$. In other words, if $ \mathbb{T} = (0,1]$, then $ \boldsymbol{\alpha} \in \mathbb{T}^n$.

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