Category: Epidemiology

Summary: Testing how aligning local susceptibility with high-mobility commuting hubs changes transient epidemic growth and reactive-mode localization.

Metapopulation epidemic models often emphasize thresholds for sustained spread, but finite-time amplification can also matter when the system is strongly non-normal. This experiment asks whether assigning higher susceptibility to the same patches that act as mobility hubs widens the transient-growth window and concentrates epidemic amplification on those hubs.

The model compares aligned, neutral, and anti-aligned assignments of susceptibility relative to commuting centrality. GPU-enabled batched sweeps then map how that correlation changes both short-term epidemic growth and localization of the reactive mode that dominates transient amplification.

That makes the project a structure-correlation study. Mobility heterogeneity and susceptibility heterogeneity are both familiar ingredients, but the experiment isolates whether their alignment is itself a separate driver of finite-time epidemic risk.

Method: GPU-accelerated metapopulation epidemic simulations and operator analyses, sweeping the correlation between local susceptibility and commuting-hub strength.

What is measured: Transient-growth window, reactive-mode localization, hub loading of the amplifying mode, and comparison of aligned versus anti-aligned susceptibility assignments.