Akdim Khadija, Ez-Zetouni Adil, Zahid Mehdi
Department of Mathematics, Faculty of Sciences and Technology, Cadi Ayyad University, B.P. 549, C.P. 40.000 Marrakesh, Morocco.
Model Earth Syst Environ. 2022;8(1):1311-1319. doi: 10.1007/s40808-021-01158-9. Epub 2021 Apr 8.
Mass-media coverage is one of the most widely used government strategies on influencing public opinion in times of crisis. Awareness campaigns are highly influential tools to expand healthy behavior practices among individuals during epidemics and pandemics. Mathematical modeling has become an important tool in analyzing the effects of media awareness on the spread of infectious diseases. In this paper, a fractional-order epidemic model incorporating media coverage is presented and analyzed. The problem is formulated using susceptible, infectious and recovered compartmental model. A long-term memory effect modeled by a Caputo fractional derivative is included in each compartment to describe the evolution related to the individuals' experiences. The well-posedness of the model is investigated in terms of global existence, positivity, and boundedness of solutions. Moreover, the disease-free equilibrium and the endemic equilibrium points are given alongside their local stabilities. By constructing suitable Lyapunov functions, the global stability of the disease-free and endemic equilibria is proven according to the basic reproduction number . Finally, numerical simulations are performed to support our analytical findings. It was found out that the long-term memory has no effect on the stability of the equilibrium points. However, for increased values of the fractional derivative order parameter, each solution reaches its equilibrium state more rapidly. Furthermore, it was observed that an increase of the media awareness parameter, decreases the magnitude of infected individuals, and consequently, the height of the epidemic peak.
大众媒体报道是政府在危机时期影响公众舆论最广泛使用的策略之一。宣传活动是在流行病和大流行期间扩大个人健康行为实践的极具影响力的工具。数学建模已成为分析媒体宣传对传染病传播影响的重要工具。本文提出并分析了一个包含媒体报道的分数阶流行病模型。该问题采用易感、感染和康复的 compartments 模型来表述。每个 compartments 中都包含由 Caputo 分数阶导数建模的长期记忆效应,以描述与个体经历相关的演变。从解的全局存在性、正性和有界性方面研究了模型的适定性。此外,给出了无病平衡点和地方病平衡点及其局部稳定性。通过构造合适的 Lyapunov 函数,根据基本再生数证明了无病平衡点和地方病平衡点的全局稳定性。最后,进行了数值模拟以支持我们的分析结果。结果发现,长期记忆对平衡点的稳定性没有影响。然而,对于分数阶导数阶参数值的增加,每个解达到其平衡状态的速度更快。此外,观察到媒体宣传参数的增加会降低感染个体的数量,从而降低疫情高峰的高度。