ABSTRACT
Age structure is one of the crucial factors in characterizing the heterogeneous epidemic transmission. Vaccination is regarded as an effective control measure for prevention and control epidemics. Due to the shortage of vaccine capacity during the outbreak of epidemics, how to design vaccination policy has become an urgent issue in suppressing the disease transmission. In this paper, we make an effort to propose an age-structured SVEIHR model with the disease-caused death to take account of dynamics of age-related vaccination policy for better understanding disease spread and control. We present an explicit expression of the basic reproduction number R 0 , which determines whether or not the disease persists, and then establish the existence and stability of endemic equilibria under certain conditions. Numerical simulations are illustrated to show that the age-related vaccination policy has a tremendous influence on curbing the disease transmission. Especially, vaccination of people over 65 is better than for people aged 21-65 in terms of rapid eradication of the disease in Italy.
Subject(s)
Epidemics , Vaccination , Humans , Disease Outbreaks/prevention & control , Basic Reproduction Number , Epidemics/prevention & control , ItalyABSTRACT
A reaction-diffusion viral infection model is formulated to characterize the infection process of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a heterogeneous environment. In the model, the viral production, infection and death rates of compartments are given by the general functions. We consider the well-posedness of the solution, derive the basic reproduction number R 0 , discuss the global stability of uninfected steady state and explore the uniform persistence for the model. We further propose a spatial diffusion SARS-CoV-2 infection model with humoral immunity and spatial independent coefficients, and analyze the global attractivity of uninfected, humoral inactivated and humoral activated equilibria which are determined by two dynamical thresholds. Numerical simulations are performed to illustrate our theoretical results which reveal that diffusion, spatial heterogeneity and incidence types have evident impact on the SARS-CoV-2 infection process which should not be neglected for experiments and clinical treatments.
ABSTRACT
This paper is devoted to studying the existence and nonexistence of traveling wave solution for a nonlocal dispersal delayed predator-prey system with the Beddington-DeAngelis functional response and harvesting. By constructing the suitable upper-lower solutions and applying Schauder's fixed point theorem, we show that there exists a positive constant $c^*$ such that the system possesses a traveling wave solution for any given $c> c^*$. Moreover, the asymptotic behavior of traveling wave solution at infinity is obtained by the contracting rectangles method. The existence of traveling wave solution for $c=c^*$ is established by means of Corduneanu's theorem. The nonexistence of traveling wave solution in the case of $c
ABSTRACT
In this paper, we are concerned with a doubly nonlinear anisotropic parabolic equation, in which the diffusion coefficient and the variable exponent depend on the time variable t. Under certain conditions, the existence of weak solution is proved by applying the parabolically regularized method. Based on a partial boundary value condition, the stability of weak solution is also investigated.
ABSTRACT
This paper discusses a class of impulsive neural networks with the variable delay and complex deviating arguments. By using Mawhin's continuation theorem of coincidence degree and the Halanay-type inequalities, several sufficient conditions for impulsive neural networks are established for the existence and globally exponential stability of periodic solutions, respectively. Furthermore, the obtained results are applied to some typical impulsive neural network systems as special cases, with a real-life example to show feasibility of our results.
Subject(s)
Models, Theoretical , Neural Networks, Computer , Population DynamicsABSTRACT
In this paper, by means of the invariance principle of differential equations, an adaptive feedback scheme is proposed to realize desynchronization in synchronous multi-coupled chaotic neurons by the mix-adaptive feedback effectively. Numerical simulations for the Hindmarsh-Rose neural model with self-coupling are illustrated which agree well with our theoretical analysis. It is observed that the feedback strengths asymptotically converge to a local fixed value in finite time, especially for linear coupling chaotic neurons with self-coupling. Furthermore, robustness of desynchronization in three coupled chaotic neurons on small mismatch of parameters is shown.
