Influence of media campaigns efforts to control spread of COVID-19 pandemic with vaccination: A modeling study

Author:

Verma Sandhya Rani1,Verma Vinay2,Pathak Rachana3,Agarwal Manju4,Naresh Ram5

Affiliation:

1. Department of Mathematics, SRM Institute of Science and Technology, Delhi-NCR Campus Ghaziabad-201204 , Uttar Pradesh , India

2. Faculty of Mathematical and Statistical Sciences, Institute of Natural Sciences and Humanities, Shri Ramswaroop Memorial University, Lucknow-Deva Road , Barabanki-225003 , Uttar Pradesh , India

3. Department of Applied Science and Humanities, Faculty of Engineering and Technology, University of Lucknow , Lucknow-226031 , Uttar Pradesh , India

4. Department of Mathematics and Astronomy, University of Lucknow , Lucknow-226007 , Uttar Pradesh , India

5. Department of Mathematics, School of Basic and Applied Sciences, Harcourt Butler Technical University , Kanpur-208007 , Uttar Pradesh , India

Abstract

Abstract The outbreak of coronavirus disease 2019 (COVID-19) has been declared a pandemic by the world health organization on March 11, 2020,. Here, a nonlinear mathematical model is proposed and analyzed to study the spread of coronavirus disease in a human habitat. In modeling the dynamics, the total population is divided into five subclasses: susceptible population, asymptomatic infective population, symptomatic infective population, recovered population, and vaccinated population. It is assumed that the disease is transmitted directly from infectives. It is further assumed that due to the effect of media, susceptible individuals become aware about the disease and avoid contact with the infectives. The analysis of the model is performed using the stability theory of differential equations. Furthermore, conditions that influence the persistence of the system are obtained. We have also conducted numerical simulations to validate the analytical results. The model analysis shows that with an increase in media awareness, the spread of coronavirus disease decreases with a decrease in the number of infective populations.

Publisher

Walter de Gruyter GmbH

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