Initial seeding of an epidemic from the best-connected nodes of a network would intuitively lead to the largest outbreak. We challenge this picture and explore a switchover phenomenon: Epidemics started from the central part of a geometric metapopulation network can reach more individuals only if the basic reproduction number is small, but if the epidemic is more infectious, it reaches a larger population when seeded from uniformly selected nodes. We identify spatial geometry to amplify this effect in both data-driven and synthetic epidemic models, and we give rigorous proofs that this phenomenon appears in various random networks. Our results help us understand why real epidemics started from seemingly similar conditions may have significantly different outcomes.
Márton Karsai's latest paper has been published in the Proceedings of the National Academy of Sciences (PNAS). This is the result of his collaboration, among others, with people from the Rényi Institute of Mathematics in Budapest.
Gergely Ódor, Domonkos Czifra, Júlia Komjáthy, László Lovász, and Márton Karsai: Switchover phenomenon induced by epidemic seeding on geometric networks. PNAS October 12, 2021 118 (41) e2112607118