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 Erdős-Rényi graphs demonstrate that our estimator achieves meaningful reconstruction accuracy despite operating on compressed observations.

翻译：我们研究独立级联模型中流行病传播过程的零号病人问题，并提出一种基于几何的源重建方法。通过Johnson-Lindenstrauss投影，我们将接触网络嵌入低维欧氏空间，并将感染源估计为最接近感染节点重心的节点。在Erdős-Rényi图上的仿真表明，尽管该方法基于压缩观测数据，我们的估计器仍能达到有意义的重建精度。