SEIR epidemic model for COVID-19 transmission by Caputo derivative of fractional order

A novel coronavirus (COVID-19), which has become a great concern for the world, was identified first in Wuhan city in China. The rapid spread throughout the world was accompanied by an alarming number of infected patients and increasing number of deaths gradually. If the number of infected cases can be predicted in advance, it would have a large contribution to controlling this pandemic in any area. Therefore, this study introduces an integrated model for predicting the number of confirmed cases from the perspective of Bangladesh. Moreover, the number of quarantined patients and the change in basic reproduction rate (the R0-value) can also be evaluated using this model. This integrated model combines the SEIR (Susceptible, Exposed, Infected, Removed) epidemiological model and neural networks. The model was trained using available data from 250 days. The accuracy of the prediction of confirmed cases is almost between 90% and 99%. The performance of this integrated model was evaluated by showing the difference in accuracy between the integrated model and the general SEIR model. The result shows that the integrated model is more accurate than the general SEIR model while predicting the number of confirmed cases in Bangladesh.

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“…Rezapour et al [9] provided a spread model of the coronavirus pandemic using SEIR. They applied the Caputo fractional derivative.…”

Section: Related Workmentioning

confidence: 99%

An Integrated Neural Network and SEIR Model to Predict COVID-19

Zisad

Hossain

et al. 2021

Algorithms

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“…In the epidemiological diseases related to viruses, mathematical modelling is very useful in studying the transmission of the disease among distinct groups because it help in managing the disease. In this section of the paper, we suggest a

paradigm for COVID-19 epidemic utilizing fractional differential equations as a generalization of the SEIR model [63] . The worldwide association of health (WHO) classifies the infected people into two types: one class with no symptoms and the other type has symptoms and both of them can transfer the virus to others.…”

Section: Mathematical Model Designmentioning

confidence: 99%

“…The parameters’ values are estimated and taken from the cited references. The world current rate of birth is 0.018, and the rate of death is 0.007612 ( [68] , [69] , [63] , [70] ). The whole population of the world on 4/2/2020 was

, as a result we have

and

.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Numerical study of fractional order COVID-19 pandemic transmission model in context of ABO blood group

2021

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“…Dynamics of a fractional order mathematical model for COVID-19 is analyzed by Rezapour et al. [8] and by Zhang et al. [9] .…”

Section: Introductionmentioning

confidence: 99%

Dynamics of SEIR epidemic model by optimal auxiliary functions method

Marinca

Bogdan

2021

Chaos, Solitons & Fractals

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The aim of the present work is to establish an approximate analytical solution for the nonlinear Susceptible, Exposed, Infected, Recovered (SEIR) model applied to novel coronavirus COVID-19. The mathematical model depending of five nonlinear differential equations, is studied and approximate solutions are obtained using Optimal Auxiliary Functions Method (OAFM). Our technique ensures a fast convergence of the solutions after only one iteration. The nonstandard part of OAFM is described by the presence of so-called auxiliary functions and of the optimal convergence-control parameters. We have a great freedom to select the auxiliary functions and the number of optimal convergence-control parameters which are optimally determined. Our approach is independent of the presence of small or large parameters in the governing equations or in the initial/boundary conditions, is effective, simple and very efficient.

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SEIR epidemic model for COVID-19 transmission by Caputo derivative of fractional order

Cited by 101 publications

References 42 publications

An Integrated Neural Network and SEIR Model to Predict COVID-19

An Integrated Neural Network and SEIR Model to Predict COVID-19

Numerical study of fractional order COVID-19 pandemic transmission model in context of ABO blood group

Dynamics of SEIR epidemic model by optimal auxiliary functions method

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