Optimal bound for survival time of the SIRS process on star graphs
Phuc Lam, Oanh Nguyen, Iris Yang

TL;DR
This paper rigorously determines the survival time bounds for the SIRS epidemic process on star graphs, confirming a conjecture and providing precise asymptotic behavior based on infection and recovery rates.
Contribution
It proves the conjectured bound for SIRS survival time on star graphs, establishing matching upper and lower bounds dependent on infection and recovery rates.
Findings
Survival time is of order $( ext{infection rate}^2 imes ext{number of leaves})^ ext{recovery rate}$.
The result holds even when only the root is immunized and leaves recover immediately.
Confirms and refines previous conjectures with rigorous bounds.
Abstract
We analyze the Susceptible-Infected-Recovered-Susceptible (SIRS) process, a continuous-time Markov chain frequently employed in epidemiology to model the spread of infections on networks. In this framework, infections spread as infected vertices recover at rate 1, infect susceptible neighbors independently at rate , and recovered vertices become susceptible again at rate . This model presents a significantly greater analytical challenge compared to the SIS model, which has consequently inspired a much more extensive and rich body of mathematical literature for the latter. Understanding the survival time, the duration before the infection dies out completely, is a fundamental question in this context. On general graphs, survival time heavily depends on the infection's persistence around high-degree vertices (known as hubs or stars), as long persistence enables…
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Taxonomy
TopicsOptimization and Search Problems · Advanced Queuing Theory Analysis · Stochastic processes and statistical mechanics
