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

Q2 Mathematics
Sandhya Rani Verma, V. Verma, Rachana Pathak, M. Agarwal, Ram Naresh
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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.
媒体宣传对通过接种疫苗控制 COVID-19 大流行传播的影响:模型研究
世界卫生组织已于 2020 年 3 月 11 日宣布 2019 年冠状病毒病(COVID-19)爆发为大流行病。本文提出并分析了一个非线性数学模型,以研究冠状病毒病在人类栖息地的传播。在建立动态模型时,总人口被分为五个子类:易感人群、无症状感染人群、有症状感染人群、康复人群和接种疫苗人群。假定疾病由感染者直接传播。此外,还假设由于媒体的影响,易感人群开始了解该疾病并避免与感染者接触。模型分析采用微分方程的稳定性理论。此外,我们还获得了影响系统持久性的条件。我们还进行了数值模拟,以验证分析结果。模型分析表明,随着媒体认知度的提高,冠状病毒疾病的传播会随着感染人群数量的减少而降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational and Mathematical Biophysics
Computational and Mathematical Biophysics Mathematics-Mathematical Physics
CiteScore
2.50
自引率
0.00%
发文量
8
审稿时长
30 weeks
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