Open Access

ARTICLE

Mathematical Analysis of Novel Coronavirus (2019-nCov) Delay Pandemic Model

Muhammad Naveed¹, Muhammad Rafiq², Ali Raza³, Nauman Ahmed⁴, Ilyas Khan^{5, *}, Kottakkaran Sooppy Nisar⁶, Atif Hassan Soori¹

1 Department of Mathematics, Air University, Islamabad, Pakistan.
2 Faculty of Engineering University of Central Punjab, Lahore, Pakistan.
3 Department of Mathematics, National College of Business Administration and Economics, Lahore, Pakistan.
4 Department of Mathematics and Statistics, The University of Lahore, Lahore, Pakistan.
5 Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh, 72915, Vietnam.
6 Department of Mathematics, College of Arts and Science at Wadi Aldawaser, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia.

* Corresponding Author: Ilyas Khan. Email: .

(This article belongs to the Special Issue: Artificial Intelligence and Information Technologies for COVID-19)

Computers, Materials & Continua 2020, 64(3), 1401-1414. https://doi.org/10.32604/cmc.2020.011314

Received 30 April 2020; Accepted 29 May 2020; Issue published 30 June 2020

Abstract

In this manuscript, the mathematical analysis of corona virus model with time delay effect is studied. Mathematical modelling of infectious diseases has substantial role in the different disciplines such as biological, engineering, physical, social, behavioural problems and many more. Most of infectious diseases are dreadful such as HIV/AIDS, Hepatitis and 2019-nCov. Unfortunately, due to the non-availability of vaccine for 2019- nCov around the world, the delay factors like, social distancing, quarantine, travel restrictions, holidays extension, hospitalization and isolation are used as key tools to control the pandemic of 2019-nCov. We have analysed the reproduction number R_nCov of delayed model. Two key strategies from the reproduction number of 2019-nCov model, may be followed, according to the nature of the disease as if it is diminished or present in the community. The more delaying tactics eventually, led to the control of pandemic. Local and global stability of 2019-nCov model is presented for the strategies. We have also investigated the effect of delay factor on reproduction number R_nCov. Finally, some very useful numerical results are presented to support the theoretical analysis of the model.

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Citations