@inproceedings{8bfbfd74-922b-4eb5-b176-d48dd6a5aff4,
  abstract     = {{<p>This paper investigates a behavioral-feedback SIR model in which the infection rate adapts dynamically based on the fractions of susceptible and infected individuals. We introduce an invariant of motion and we characterize the peak of infection. We further examine the system under a threshold constraint on the infection level. Based on this analysis, we formulate an optimal control problem to keep the infection curve below a healthcare capacity threshold while minimizing the economic cost. For this problem, we study a feasible strategy that involves applying the minimal necessary restrictions to meet the capacity constraint and characterize the corresponding cost.</p>}},
  author       = {{Alutto, Martina and Cianfanelli, Leonardo and Como, Giacomo and Fagnani, Fabio and Parise, Francesca}},
  booktitle    = {{2025 IEEE 64th Conference on Decision and Control, CDC 2025}},
  isbn         = {{9798331526276}},
  issn         = {{2576-2370}},
  keywords     = {{Epidemic models; Optimal control problem; Susceptible-Infected-Recovered model}},
  language     = {{eng}},
  pages        = {{3615--3621}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{Proceedings of the IEEE Conference on Decision and Control}},
  title        = {{Behavioral-feedback SIR epidemic model : Analysis and control}},
  url          = {{http://dx.doi.org/10.1109/CDC57313.2025.11312680}},
  doi          = {{10.1109/CDC57313.2025.11312680}},
  year         = {{2025}},
}