The SAITS epidemic spreading model and its combinational optimal suppression control.

Area of Science:

• Epidemiology
• Mathematical Modeling
• Network Science

Background:

• Epidemic modeling is crucial for understanding disease dynamics.
• Static network models offer a framework for analyzing disease spread.
• Control strategies are essential for mitigating epidemic impact.

Purpose of the Study:

• To propose and investigate a Susceptible-Asymptomatic-Infected-Transferred-Susceptible (SAITS) epidemic model on a static network.
• To develop and analyze a combinational suppression control strategy.
• To formulate an optimal control problem for minimizing infections.

Main Methods:

• Development of an SAITS epidemic model.
• Calculation of the basic reproduction number.
• Analysis of disease-free and endemic equilibrium points.
• Formulation of an optimal control problem using Pontryagin's principle.
• Numerical and Monte Carlo simulations for validation.

Main Results:

• The SAITS model and its equilibrium points were analyzed.
• A combinational suppression strategy involving compartment transfer was proposed.
• An optimal control strategy was derived to minimize infections.
• Theoretical results were validated through simulations.

Conclusions:

• The proposed SAITS model provides a framework for studying epidemic dynamics on networks.
• The combinational suppression strategy is effective in controlling disease spread.
• Optimal control methods can be applied to resource-limited epidemic management.