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SIR Epidemics on Evolving Erd\H{o}s-R\'enyi Graphs

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arxiv 2208.11923 v2 pith:B25LCQRA submitted 2022-08-25 math.PR

classification math.PR
keywords modellambdaomegaratesir-alphacitediscontinuous
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abstract

In the standard SIR model, infected vertices infect their neighbors at rate $\lambda$ independently across each edge. They also recover at rate $\gamma$. In this work we consider the SIR-$\omega$ model where the graph structure itself co-evolves with the SIR dynamics. Specifically, $S-I$ connections are broken at rate $\omega$. Then, with probability $\alpha$, $S$ rewires this edge to another uniformly chosen vertex; and with probability $1-\alpha$, this edge is simply dropped. When $\alpha=1$ the SIR-$\omega$ model becomes the evoSIR model. Jiang et al. proved in \cite{DOMath} that the probability of an outbreak in the evoSIR model converges to 0 as $\lambda$ approaches the critical infection rate $\lambda_c$. On the other hand, numerical experiments in \cite{DOMath} revealed that, as $\lambda \to \lambda_c$, (conditionally on an outbreak) the fraction of infected vertices may not converge to 0, which is referred to as a discontinuous phase transition. In \cite{BB} Ball and Britton give two (non-matching) conditions for continuous and discontinuous phase transitions for the fraction of infected vertices in the SIR-$\omega$ model. In this work, we obtain a necessary and sufficient condition for the emergence of a discontinuous phase transition of the final epidemic size of the SIR-$\omega$ model on \ER\, graphs, thus closing the gap between these two conditions.

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  1. Stochastic heterogeneous SIR model with infection-age dependent infectivity on large random graphs

    math.PR 2025-02 conditional novelty 7.0 of 10

    A functional law of large numbers is proved for non-Markovian SIR epidemics with infection-age-dependent infectivity on large heterogeneous random graphs, with a graphon PDE as the limit.

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