Mathematical Properties of Strategies to Control Epidemic Outbreaks in the Context of SEIR Models with Multiple Infectious Stages
Annibal Figueiredo, Tarc{\i}sio Marciano da Rocha Filho

TL;DR
This paper mathematically analyzes control strategies in SEIR epidemic models with multiple infectious stages, revealing limits on infection reduction and the importance of timing and duration of interventions, exemplified with COVID-19.
Contribution
It introduces a mathematical framework for control strategies in complex SEIR models, showing how they influence epidemic dynamics and long-term infection limits.
Findings
Control strategies lead to non-autonomous differential systems.
There exists a maximum susceptible population at attractors, limiting infections.
Timing and duration of control significantly affect epidemic outcomes.
Abstract
In this work we analyze mathematically the consequences and effectiveness of strategies to control an epidemic in the framework of classical SEIR models with multiple parallel infectious stages. We define the mathematical concept of a control strategy, showing that it implies turning classic epidemiological models into systems of non-autonomous differential equations. The analysis of these non-autonomous systems is based on the two main results obtained in this work: the first establishes a condition that implies a dynamic without epidemic outbreaks; the second establishes a maximum value for the susceptible population associated to the fixed points that are attractors, moreover, we proof that any trajectory converges to some of these attractors. An important consequence of this last result is the existence of an insurmountable limit on the number of infected individuals after the end…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models · Evolution and Genetic Dynamics
