Proportional hazards models of infrastructure system recovery

As emphasis is being placed on a systemʹs ability to withstand and to recover from a disruptive event, collectively referred to as dynamic resilience, there exists a need to quantify a systemʹs ability to bounce back after a disruptive event. This work applies a statistical technique from biostatistics, the proportional hazards model, to describe (i) the instantaneous rate of recovery of an infrastructure system and (ii) the likelihood that recovery occurs prior to a given point in time. A major benefit of the proportional hazards model is its ability to describe a recovery event as a function of time as well as covariates describing the infrastructure system or disruptive event, among others, which can also vary with time. The proportional hazards approach is illustrated with a publicly available electric power outage data set.