The study demonstrates the asymptotic height of the infection tree in stochastic SIR models, suggesting a second-order phase transition for infections.
We are interested in the geometry of the ``infection tree'' in a stochastic SIR (Susceptible-Infectious-Recovered) model, starting with a single infectious individual. This tree is constructed by drawing an edge between two individuals when one infects the other. We focus on the regime where the infectious period before recovery follows an exponential distribution with rate $1$, and infections occur at a rate λₙ ~ λ/n where n is the initial number of healthy individuals with λ>1. We show that provided that the infection does not quickly die out, the height of the infection tree is asymptotically κ(λ) log n as n → ∞, where κ(λ) is a continuous function in λ that undergoes a second-order phase transition at λc 1.8038. Our main tools include a connection with the model of uniform attachment trees with freezing and the application of martingale techniques to control profiles of random trees.
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Kammerer et al. (2025) studied this question.
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