Advanced Control in Epidemics: a Practical Identification Algorithm for Extended SVIR Models with Vaccination and Social Mobility Control

Abstract

Humanity has historical events of epidemics and pandemics that have caused millions of deaths and have had a devastating impact on the economy, public health, education, and social life. In this context, researchers from different areas have investigated solutions that mitigate the effects and spread of the virus in epidemics/pandemics. In this paper, an identification algorithm is proposed for an epidemiological model with two doses of vaccination that considers social mobility as a control variable (stringency index). In addition, a practical model is developed in order to ensure the applicability of the system since much of the data is not reported in epidemics. Therefore, the identification algorithm is composed mainly of the practical equivalent model, discrete analytical solution for the observable compartments, adaptive variable, and optimization. As a result, the system was validated by simulations and was incorporated into an optimal control strategy, improving its robustness in a hypothetical scenario of an epidemic.