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Mathematical model for the novel coronavirus (2019-nCOV) with clinical data using fractional operator.
El-Sayed, Ahmed M A; Arafa, Anas; Hagag, Ahmed.
  • El-Sayed AMA; Department of Mathematics, Faculty of Science Alexandria University Alexandria Egypt.
  • Arafa A; Department of Mathematics, College of Science and Arts Qassim University Al Mithnab Saudi Arabia.
  • Hagag A; Department of Mathematics and Computer Science, Faculty of Science Port Said University Port Said Egypt.
Numer Methods Partial Differ Equ ; 2022 Sep 12.
Article in English | MEDLINE | ID: covidwho-2227136
ABSTRACT
Coronavirus infection (COVID-19) is a considerably dangerous disease with a high demise rate around the world. There is no known vaccination or medicine until our time because the unknown aspects of the virus are more significant than our theoretical and experimental knowledge. One of the most effective strategies for comprehending and controlling the spread of this epidemic is to model it using a powerful mathematical model. However, mathematical modeling with a fractional operator can provide explanations for the disease's possibility and severity. Accordingly, basic information will be provided to identify the kind of measure and intrusion that will be required to control the disease's progress. In this study, we propose using a fractional-order SEIARPQ model with the Caputo sense to model the coronavirus (COVID-19) pandemic, which has never been done before in the literature. The stability analysis, existence, uniqueness theorems, and numerical solutions of such a model are displayed. All results were numerically simulated using MATLAB programming. The current study supports the applicability and influence of fractional operators on real-world problems.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Year: 2022 Document Type: Article