Cascading-Failure Resilience Index

Critical infrastructures increasingly function as tightly coupled systems in which local shocks can propagate across sectors. Existing national resilience indices emphasize static capacity such as sectoral quality, redundancy, or governance, but they rarely capture dynamic cascading behavior. This codebase introduces the Cascading Failure Resilience Index (CFRI), a hybrid metric that combines a static Structural Stability Index (SSI), derived from normalized infrastructure indicators across multiple dimensions, with a Dynamic Propagation Index (DPI). The dynamic component is produced through a discrete time simulation of shock spread over an interdependency network.

CFRI v1.0 covers seven sectors (power, telecom, water, transport, health, finance, and public safety) and four resilience dimensions (redundancy, shielding, recovery, and adaptivity). Indicator data are normalized using a hybrid absolute and relative scheme. Dimension scores map to dynamic buffers that determine protection, redundancy, recovery speed, and adaptivity. Shocks are introduced through scenario definitions with sector specific initial losses and time horizons. Dynamic outcomes such as cascade depth, deficit area, recovery time, and reach are scaled with the same hybrid scheme and then combined to form DPI.

We provide an open source Python implementation, and a demonstration on a multi country sample that spans diverse resilience contexts. All regions in the example are evaluated jointly so that relative components are defined over the shared distribution. Sensitivity tests show that CFRI rankings remain stable under reasonable parameter changes. CFRI is intended as a transparent and extensible framework for comparative resilience analysis, and all code and data templates are included to support reproducibility.