Control of Overpopulated Tails in Kinetic Epidemic Models
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909692974858240 |
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| author | Zanella, Mattia Medaglia, Andrea |
| author_facet | Zanella, Mattia Medaglia, Andrea |
| contents | We introduce model-based transition rates for controlled compartmental models in mathematical epidemiology, with a focus on the effects of control strategies applied to interacting multi-agent systems describing contact formation dynamics. In the framework of kinetic control problems, we compare two prototypical control protocols: one additive control directly influencing the dynamics and another targeting the interaction strength between agents. The emerging controlled macroscopic models are derived for an SIR compartmentalization to illustrate their impact on epidemic progression and contact interaction dynamics. Numerical results show the effectiveness of this approach in steering the dynamics and controlling epidemic trends, even in scenarios where contact distributions exhibit an overpopulated tail. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2501_05365 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Control of Overpopulated Tails in Kinetic Epidemic Models Zanella, Mattia Medaglia, Andrea Optimization and Control Adaptation and Self-Organizing Systems Physics and Society Populations and Evolution We introduce model-based transition rates for controlled compartmental models in mathematical epidemiology, with a focus on the effects of control strategies applied to interacting multi-agent systems describing contact formation dynamics. In the framework of kinetic control problems, we compare two prototypical control protocols: one additive control directly influencing the dynamics and another targeting the interaction strength between agents. The emerging controlled macroscopic models are derived for an SIR compartmentalization to illustrate their impact on epidemic progression and contact interaction dynamics. Numerical results show the effectiveness of this approach in steering the dynamics and controlling epidemic trends, even in scenarios where contact distributions exhibit an overpopulated tail. |
| title | Control of Overpopulated Tails in Kinetic Epidemic Models |
| topic | Optimization and Control Adaptation and Self-Organizing Systems Physics and Society Populations and Evolution |
| url | https://arxiv.org/abs/2501.05365 |