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arXiv · 2604.16074

Finding Patient Zero via Low-Dimensional Geometric Embeddings

Stefan Huber·Dominik Kaaser
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Abstract

We study the patient zero problem in epidemic spreading processes in the independent cascade model and propose a geometric approach for source reconstruction. Using Johnson-Lindenstrauss projections, we embed the contact network into a low-dimensional Euclidean space and estimate the infection source as the node closest to the center of gravity of infected nodes. Simulations on Erd\H{o}s-R\'enyi graphs demonstrate that our estimator achieves meaningful reconstruction accuracy despite operating on compressed observations.

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Stefan Huber, Dominik Kaaser. 2026-04-17. Finding Patient Zero via Low-Dimensional Geometric Embeddings. https://arxiv.org/abs/2604.16074

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