On the modeling of epidemics under the influence of risk perception-Reference-Cited by-同舟云学术

On the modeling of epidemics under the influence of risk perception

Published:2017-04 Issue:04 Volume:28 Page:1750051
ISSN:0129-1831
Container-title:International Journal of Modern Physics C
language:en
Short-container-title:Int. J. Mod. Phys. C

Author:

De Lillo S.¹²,Fioriti G.²³,Prioriello M. L.⁴⁵

Affiliation:

1. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli 1, 06123 Perugia, Italy

2. Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, Italy

3. Department of Mathematics and Computer Science Ulisse Dini, University of Florence, viale Morgagni 67/A, 50134 Florence, Italy

4. Department of Mathematics and Computer Science, Eindhoven University of Technology, P. O. Box 513, 5600 MB Eindhoven, The Netherlands

5. Department of Mathematics, Physics and Computer Science, University of Modena and Reggio Emilia, via G. Campi 213/b, 41125 Modena, Italy

Abstract

An epidemic spreading model is presented in the framework of the kinetic theory of active particles. The model is characterized by the influence of risk perception which can reduce the diffusion of infection. The evolution of the system is modeled through nonlinear interactions, whose output is described by stochastic games. The results of numerical simulations are discussed for different initial conditions.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0129183117500516

Reference31 articles.

1. Stochastic Epidemic Models and Their Statistical Analysis

2. The Influence of Risk Perception in Epidemics: A Cellular Agent Model

3. Analysis of a stochastic SIR epidemic on a random network incorporating household structure

4. The distribution of general final state random variables for stochastic epidemic models

5. Modelling and mathematical problems related to tumor evolution and its interaction with the immune system

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