Network metrics for bridge prioritization considering bridge condition, accessibility, equity and uncertainty

Traditional methods for bridge prioritization often rely on structural assessments or traffic volumes, overlooking localized accessibility impacts and broader network-wide disruptions. They also require large amounts of historical data which may not be available. These approaches tend to miss how bridge failures affect connectivity and accessibility time to essential services. This study introduces a diagnostic framework that integrates classical metrics: Population-Weighted Betweenness Centrality (PWBC), Average Annual Daily Traffic (AADT) with a Efficiency Sensitivity (ES) metric to evaluate bridge importance based on accessibility time loss under probabilistic failure scenarios. Using Monte Carlo simulations and population-weighted metrics, we assessed service-specific vulnerabilities in Spartanburg County, South Carolina, focusing on access to hospitals and grocery stores. Results reveal that some low-traffic bridges play a disproportionately large role in maintaining access, especially for peri-urban and vulnerable communities. For instance, while grocery access saw only a 0.31% drop in global efficiency under full disruption, hospital access declined by 1.30%, revealing service-type sensitivity. The Efficiency Sensitivity metric, combined with threshold detection using the Kneedle algorithm, provides a practical and scalable tool for identifying hidden critical infrastructure. Equity analysis revealed that Environmental Justice (EJ) and rural communities experience disproportionate hazard impacts. This framework offers transportation agencies a more equitable and resilience-informed basis for prioritizing limited maintenance resources and strengthening service continuity across diverse communities.