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Epidemics on critical random graphs with heavy-tailed degree distribution

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  • Clancy, David

Abstract

We study the susceptible–infected–recovered (SIR) epidemic on a random graph chosen uniformly over all graphs with certain critical, heavy-tailed degree distributions. We prove process level scaling limits for the number of individuals infected on day h on the largest connected components of the graph. The scaling limits contain non-negative jumps corresponding to some vertices of large degree. These weak convergence techniques allow us to describe the height profile of the α-stable continuum random graph (Goldschmidt et al., 2022; Conchon-Kerjan and Goldschmidt, 2023), extending results known in the Brownian case (Miermont and Sen, 2022). We also prove model-independent results that can be used on other critical random graph models.

Suggested Citation

  • Clancy, David, 2025. "Epidemics on critical random graphs with heavy-tailed degree distribution," Stochastic Processes and their Applications, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:spapps:v:179:y:2025:i:c:s0304414924002187
    DOI: 10.1016/j.spa.2024.104510
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