Multiple peaks in network SIR epidemic models

Como, Giacomo (författare): Lund University,Lunds universitet,Institutionen för reglerteknik,Institutioner vid LTH,Lunds Tekniska Högskola,LTH profilområde: AI och digitalisering,LTH profilområden,Department of Automatic Control,Departments at LTH,Faculty of Engineering, LTH,LTH Profile Area: AI and Digitalization,LTH Profile areas,Faculty of Engineering, LTH,Polytechnic University of Turin

(creator_code:org_t)

2022
2022
Engelska 6 s.
Ingår i: 2022 IEEE 61st Conference on Decision and Control, CDC 2022. - 2576-2370 .- 0743-1546. - 9781665467612 ; 2022-December, s. 5614-5619

Relaterad länk:: http://dx.doi.org/10...; visa fler...; https://lup.lub.lu.s...; https://doi.org/10.1...; visa färre...

Abstract Ämnesord

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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.

Av författaren/redakt...: Alutto, Martina; Cianfanelli, Leo ...; Como, Giacomo; Fagnani, Fabio

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