Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative

Pandey, Prashant and Gomez-Aguilar, J. F. and Kaabar, Mohammed K. A. and Siri, Zailan and Mousa, Abd Allah A. (2022) Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative. Computers in Biology and Medicine, 145. ISSN 0010-4825, DOI

Full text not available from this repository.


The range of effectiveness of the novel corona virus, known as COVID-19, has been continuously spread worldwide with the severity of associated disease and effective variation in the rate of contact. This paper investigates the COVID-19 virus dynamics among the human population with the prediction of the size of epidemic and spreading time. Corona virus disease was first diagnosed on January 30, 2020 in India. From January 30, 2020 to April 21, 2020, the number of patients was continuously increased. In this scientific work, our main objective is to estimate the effectiveness of various preventive tools adopted for COVID-19. The COVID-19 dynamics is formulated in which the parameters of interactions between people, contact tracing, and average latent time are included. Experimental data are collected from April 15, 2020 to April 21, 2020 in India to investigate this virus dynamics. The Genocchi collocation technique is applied to investigate the proposed fractional mathematical model numerically via Caputo-Fabrizio fractional derivative. The effect of presence of various COVID parameters e.g. quarantine time is also presented in the work. The accuracy and efficiency of the outputs of the present work are demonstrated through the pictorial presentation by comparing it to known statistical data. The real data for COVID-19 in India is compared with the numerical results obtained from the concerned COVID-19 model. From our results, to control the expansion of this virus, various prevention measures must be adapted such as self-quarantine, social distancing, and lockdown procedures.

Item Type: Article
Funders: CONACyT: Catedras CONACyT para jovenes investigadores, Consejo Nacional de Ciencia y Tecnologia (CONACyT)
Uncontrolled Keywords: Infectious diseases; COVID-19; Caputo-fabrizio fractional derivative; Model prediction; Pandemic slow down; Collocation technique; Genocchi polynomial
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 16 Oct 2023 05:57
Last Modified: 24 Oct 2023 03:30

Actions (login required)

View Item View Item