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A fractional-order model for the novel coronavirus (COVID-19) outbreak
- Source :
- Nonlinear Dynamics
- Publication Year :
- 2020
- Publisher :
- Springer Netherlands, 2020.
-
Abstract
- The outbreak of the novel coronavirus (COVID-19), which was firstly reported in China, has affected many countries worldwide. To understand and predict the transmission dynamics of this disease, mathematical models can be very effective. It has been shown that the fractional order is related to the memory effects, which seems to be more effective for modeling the epidemic diseases. Motivated by this, in this paper, we propose fractional-order susceptible individuals, asymptomatic infected, symptomatic infected, recovered, and deceased (SEIRD) model for the spread of COVID-19. We consider both classical and fractional-order models and estimate the parameters by using the real data of Italy, reported by the World Health Organization. The results show that the fractional-order model has less root-mean-square error than the classical one. Finally, the prediction ability of both of the integer- and fractional-order models is evaluated by using a test data set. The results show that the fractional model provides a closer forecast to the real data.
- Subjects :
- Computer science
Aerospace Engineering
Ocean Engineering
SEIRD model
medicine.disease_cause
01 natural sciences
law.invention
Set (abstract data type)
Order (exchange)
law
0103 physical sciences
Statistics
medicine
Fractional-order derivative
Electrical and Electronic Engineering
010301 acoustics
Coronavirus
Original Paper
Mathematical model
Applied Mathematics
Mechanical Engineering
Outbreak
COVID-19
Transmission (mechanics)
Control and Systems Engineering
Integer (computer science)
Test data
Subjects
Details
- Language :
- English
- ISSN :
- 1573269X and 0924090X
- Database :
- OpenAIRE
- Journal :
- Nonlinear Dynamics
- Accession number :
- edsair.doi.dedup.....26ee56ce918613c07665239464b2db56