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Behavioral-feedback SIR epidemic model : Analysis and control

Alutto, Martina ; Cianfanelli, Leonardo ; Como, Giacomo LU ; Fagnani, Fabio and Parise, Francesca (2025) 64th IEEE Conference on Decision and Control, CDC 2025 In Proceedings of the IEEE Conference on Decision and Control p.3615-3621
Abstract

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.

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author
; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Epidemic models, Optimal control problem, Susceptible-Infected-Recovered model
host publication
2025 IEEE 64th Conference on Decision and Control, CDC 2025
series title
Proceedings of the IEEE Conference on Decision and Control
pages
7 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
64th IEEE Conference on Decision and Control, CDC 2025
conference location
Rio de Janeiro, Brazil
conference dates
2025-12-09 - 2025-12-12
external identifiers
  • scopus:105031901604
ISSN
2576-2370
0743-1546
ISBN
9798331526276
DOI
10.1109/CDC57313.2025.11312680
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 IEEE.
id
8bfbfd74-922b-4eb5-b176-d48dd6a5aff4
date added to LUP
2026-05-11 15:13:56
date last changed
2026-05-25 16:11:18
@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}},
}