Category: Epidemiology

Summary: Asking whether adaptive distancing on a fractal contact network works best at an intermediate delay, balancing prevalence reduction against extinction efficiency.

Disease spread on fragmented or scale-irregular contact structures can behave differently from spread on ordinary lattices. This experiment builds a Sierpinski-carpet-like contact graph and asks whether delayed adaptive distancing creates a re-entrant control window for suppressing SIS transmission.

The code generates the fractal network, runs SIS outbreaks, and compares prevalence reduction, extinction gain, and efficiency gain across several control delays. It tracks not only whether prevalence falls, but whether the intervention achieves that reduction efficiently enough to justify its timing.

This is useful because public-health response often cannot be immediate. Identifying a center-delay advantage would show that network geometry and control lag can interact in a structured way, rather than merely penalizing every delay equally.

Method: SIS simulations on a graph derived from a Sierpinski-carpet mask, with adaptive distancing policies compared across multiple delays.

What is measured: Best delay, prevalence gain, extinction gain, efficiency gain, adaptive-delay-window signal, and center-delay advantage.