AccES: A Framework for Predicting Building-Level Loss of Accessibility to Essential Services Post-Disasters Based on Publicly Available Information.

Natural hazards significantly disrupt access to essential services, affecting individuals' capacity to withstand and recover from such events. However, existing hazard resilience models often fail to account for the interdependencies among essential services and lack the spatial resolution needed to assess accessibility loss at the building level. This study introduces the Predicting Loss of Access to Essential Services (AccES) framework-a novel, data-driven, and people-centered approach that uses publicly available information to evaluate accessibility following a natural hazard event. The framework integrates open-source datasets with local stakeholder knowledge to develop spatially explicit models of interconnected infrastructure networks, including power, water, and communication networks, along with their dependent service facilities such as hospitals, childcare centers, and grocery stores. Accessibility loss is assessed by evaluating the disruptions to infrastructure networks and service facilities, estimating (1) the probability that individual buildings lose access to infrastructure services and (2) the expected increase in travel distance to the nearest operational service facility. To demonstrate the framework's utility, a case study was conducted in Cayey, Puerto Rico, simulating the impacts of a Category 2 tropical cyclone. Results highlight spatial disparities in accessibility loss, with rural and socially vulnerable areas facing greater burdens. AccES advances hazard resilience modeling by providing a scalable, equity-oriented tool to support data-informed decision-making for both pre-disaster planning and post-disaster response.