On SIR epidemic models with feedback-controlled interactions and network effects
(2021) 2021 60th IEEE Conference on Decision and Control (CDC) p.5562-5567- Abstract
- We study extensions of the classical SIR model of epidemic spread. First, we consider a single population modified SIR epidemics model in which the contact rate is allowed to be an arbitrary function of the fraction of susceptible and infected individuals. This allows one to model either the reaction of individuals to the information about the spread of the disease or the result of government restriction measures, imposed to limit social interactions and contain contagion. We study the effect of both smooth dependancies and discontinuities of the contact rate. In the first case, we prove the existence of a threshold phenomenon that generalizes the well-known dichotomy associated to the reproduction rate parameter in the classical SIR... (More)
- We study extensions of the classical SIR model of epidemic spread. First, we consider a single population modified SIR epidemics model in which the contact rate is allowed to be an arbitrary function of the fraction of susceptible and infected individuals. This allows one to model either the reaction of individuals to the information about the spread of the disease or the result of government restriction measures, imposed to limit social interactions and contain contagion. We study the effect of both smooth dependancies and discontinuities of the contact rate. In the first case, we prove the existence of a threshold phenomenon that generalizes the well-known dichotomy associated to the reproduction rate parameter in the classical SIR model. Then, we analyze discontinuous feedback terms using tools from sliding mode control. Finally, we consider network SIR models involving different subpopulations that interact on a contact graph and present some preliminary simulations of modified versions of the classic SIR network. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8eda135f-298e-4ed9-9fc0-aea53dd1bed9
- author
- Alutto, Martina ; Como, Giacomo LU and Fagnani, Fabio
- organization
- publishing date
- 2021-12-14
- type
- Contribution to conference
- publication status
- published
- subject
- pages
- 5562 - 5567
- conference name
- 2021 60th IEEE Conference on Decision and Control (CDC)
- conference dates
- 2021-12-14 - 2021-12-17
- external identifiers
-
- scopus:85126028783
- DOI
- 10.1109/CDC45484.2021.9683007
- project
- Dynamics of Complex Socio-Technological Network Systems
- language
- English
- LU publication?
- yes
- id
- 8eda135f-298e-4ed9-9fc0-aea53dd1bed9
- alternative location
- https://ieeexplore.ieee.org/document/9683007/
- date added to LUP
- 2022-02-14 17:31:42
- date last changed
- 2022-05-07 00:23:38
@misc{8eda135f-298e-4ed9-9fc0-aea53dd1bed9,
abstract = {{We study extensions of the classical SIR model of epidemic spread. First, we consider a single population modified SIR epidemics model in which the contact rate is allowed to be an arbitrary function of the fraction of susceptible and infected individuals. This allows one to model either the reaction of individuals to the information about the spread of the disease or the result of government restriction measures, imposed to limit social interactions and contain contagion. We study the effect of both smooth dependancies and discontinuities of the contact rate. In the first case, we prove the existence of a threshold phenomenon that generalizes the well-known dichotomy associated to the reproduction rate parameter in the classical SIR model. Then, we analyze discontinuous feedback terms using tools from sliding mode control. Finally, we consider network SIR models involving different subpopulations that interact on a contact graph and present some preliminary simulations of modified versions of the classic SIR network.}},
author = {{Alutto, Martina and Como, Giacomo and Fagnani, Fabio}},
language = {{eng}},
month = {{12}},
pages = {{5562--5567}},
title = {{On SIR epidemic models with feedback-controlled interactions and network effects}},
url = {{http://dx.doi.org/10.1109/CDC45484.2021.9683007}},
doi = {{10.1109/CDC45484.2021.9683007}},
year = {{2021}},
}