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A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections
A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections
Alma Y. Alanis
(CUCEI—University Center of Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara 44430, Mexico)
Gustavo Munoz-Gomez
(Tecnologico Nacional de Mexico, Campus Nochistlan, Nochistlan 99900, Mexico)
Nancy F. Ramirez
(CUCSUR—University Center of the South Coast, Universidad de Guadalajara, Guadalajara 44100, Mexico)
Oscar D. Sanchez
(CUCEI—University Center of Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara 44430, Mexico)
Jesus G. Alvarez
(CUCEI—University Center of Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara 44430, Mexico)
Journal: Algorithms
•
• MDPI AG
• ISSN: 1999-4893
Abstract
This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an online-trained neural identifier to control the spread of infectious diseases under a complex network approach with time-varying connections where each node represents a population of individuals whose dynamics are defined by the MSEIR epidemiological model. Considering an unknown model of the system, a neural identifier is designed that provides a nonlinear model for the complex network trained through an extended Kalman filter algorithm. Simulation results are presented by applying the proposed control scheme for a complex network parameterized as infectious diseases.
Alma Y. Alanis, Gustavo Munoz-Gomez, Nancy F. Ramirez, et al. (2024). "A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections". Algorithms. https://doi.org/10.3390/a17120577