Replication code and datasets: A Practical Hierarchy of Degree-Based Estimators and Spectral Bounds for the Basic Reproduction Number on Contact Networks

This repository contains the replication code and datasets for the paper:

"A Practical Hierarchy of Degree-Based Estimators and Spectral Bounds for the Basic Reproduction Number on Contact Networks" Etienne Kouokam (2026), submitted to Journal of Complex Networks, Oxford University Press.

The script validate_hierarchy.py reproduces all numerical results, tables, and figures of the manuscript. It validates a partial analytical hierarchy of five degree-based estimators (L1, L2, Rd, U1, U3) for the spectral radius λ1(A), which governs R0 in network-based SIS/SIR models via R0 = (β/μ)·λ1(A).

Contents: Python replication script, MIT license, and CSV edge lists and degree sequences for 6 benchmark networks (Karate club, Les Misérables, Florentine families, Davis Southern Women, Barabási-Albert n=200, Erdős-Rényi n=150).

Requirements: Python 3.8+, networkx, numpy, scipy, matplotlib. Run: python validate_hierarchy.py