A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections

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 Aerosol Deodorant 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 Accessories algorithm.Simulation results are presented by applying the proposed control scheme for a complex network parameterized as infectious diseases.