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Safety-Critical Control of Compartmental Epidemiological Models With Measurement Delays
Tamas G Molnar1,2, Andrew W Singletary2, Gabor Orosz1,3
1Department of Mechanical EngineeringUniversity of Michigan Ann Arbor MI 48109 USA.
IEEE Control Systems Letters
|November 17, 2023
Summary
This study presents a new method to control infectious disease spread by treating epidemiological models as control systems. It ensures safety by managing interventions to keep populations within safe limits, even with delays.
Area of Science:
- Epidemiology
- Control Systems Engineering
- Public Health
Background:
- Infectious disease modeling is crucial for public health.
- Existing models may not inherently guarantee safety against disease spread.
- Human interventions are key but their impact needs formal control.
Purpose of the Study:
- To develop a methodology for guaranteeing safety in epidemiological models.
- To design controllers for managing human interventions and their impact.
- To address the effects of delays on safety and propose compensation methods.
Main Methods:
- Viewing epidemiological models as generalized compartmental control systems.
- Designing safety-critical controllers to maintain populations within prescribed limits.
- Analyzing the impact of measurement delays (incubation, testing) and using predictor feedback.
Main Results:
- Formal guarantees for safe evolution of disease spread under interventions.
- Demonstration of delay compensation techniques for enhanced safety.
- Synthesis of active intervention policies to bound infections, hospitalizations, and deaths.
Conclusions:
- A novel control-theoretic framework can ensure safety in infectious disease management.
- Predictor feedback effectively compensates for delays in epidemiological surveillance.
- This methodology provides a robust approach for real-world pandemic response, as shown for COVID-19 in the USA.
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