Finding Patient Zero via Low-Dimensional Geometric Embeddings

For researchers in network epidemiology, this provides a computationally efficient geometric approach to source localization, though it is incremental as it applies known dimensionality reduction to a known problem.

The paper tackles the patient zero problem in epidemic spreading under the independent cascade model, proposing a geometric method using Johnson-Lindenstrauss projections to embed the contact network into low-dimensional space and estimate the source as the node closest to the center of gravity of infected nodes. Simulations on Erdős-Rényi graphs show meaningful reconstruction accuracy with compressed observations.