Multiple peaks in network SIR epidemic models
(2022) 61st IEEE Conference on Decision and Control, CDC 2022 In Proceedings of the IEEE Conference on Decision and Control 2022-December. p.5614-5619- Abstract
We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially increasing, until reaching a peak and decreasing everafter), we show the possible occurrence of a novel multimodal behaviors in the network SIR model. Specifically, we show that the curve of the fraction of infected individuals in a population may incur in a change of monotonicity even when it starts with a decreasing trend. Our analysis... (More)
We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially increasing, until reaching a peak and decreasing everafter), we show the possible occurrence of a novel multimodal behaviors in the network SIR model. Specifically, we show that the curve of the fraction of infected individuals in a population may incur in a change of monotonicity even when it starts with a decreasing trend. Our analysis focuses on a homogeneous mixing model, whereby all contacts have unitary frequency. We study the initial conditions and network characteristics sufficient for the aforementioned multimodal behavior to emerge and those that instead guarantee the classical unimodal behavior.
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- author
- Alutto, Martina ; Cianfanelli, Leonardo ; Como, Giacomo LU and Fagnani, Fabio
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Epidemic models, reproduction number, Susceptible-Infected-Recovered model
- host publication
- 2022 IEEE 61st Conference on Decision and Control, CDC 2022
- series title
- Proceedings of the IEEE Conference on Decision and Control
- volume
- 2022-December
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 61st IEEE Conference on Decision and Control, CDC 2022
- conference location
- Cancun, Mexico
- conference dates
- 2022-12-06 - 2022-12-09
- external identifiers
-
- scopus:85147016007
- ISSN
- 2576-2370
- 0743-1546
- ISBN
- 9781665467612
- DOI
- 10.1109/CDC51059.2022.9992408
- language
- English
- LU publication?
- yes
- id
- 0d771736-b702-456f-b4b4-4ecca73986b4
- date added to LUP
- 2023-02-14 11:39:38
- date last changed
- 2024-12-13 20:16:05
@inproceedings{0d771736-b702-456f-b4b4-4ecca73986b4,
abstract = {{<p>We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially increasing, until reaching a peak and decreasing everafter), we show the possible occurrence of a novel multimodal behaviors in the network SIR model. Specifically, we show that the curve of the fraction of infected individuals in a population may incur in a change of monotonicity even when it starts with a decreasing trend. Our analysis focuses on a homogeneous mixing model, whereby all contacts have unitary frequency. We study the initial conditions and network characteristics sufficient for the aforementioned multimodal behavior to emerge and those that instead guarantee the classical unimodal behavior.</p>}},
author = {{Alutto, Martina and Cianfanelli, Leonardo and Como, Giacomo and Fagnani, Fabio}},
booktitle = {{2022 IEEE 61st Conference on Decision and Control, CDC 2022}},
isbn = {{9781665467612}},
issn = {{2576-2370}},
keywords = {{Epidemic models; reproduction number; Susceptible-Infected-Recovered model}},
language = {{eng}},
pages = {{5614--5619}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{Proceedings of the IEEE Conference on Decision and Control}},
title = {{Multiple peaks in network SIR epidemic models}},
url = {{http://dx.doi.org/10.1109/CDC51059.2022.9992408}},
doi = {{10.1109/CDC51059.2022.9992408}},
volume = {{2022-December}},
year = {{2022}},
}