Evaluating education disruption by integrated school and road infrastructure system analysis

Public education is considered a fundamental service governments should offer to their population. Nonetheless, in the occurrence of natural hazard events, it is often disrupted, as the school infrastructure gets damaged. Besides the physical damage to school buildings, factors such as the inability to commute also affect the capacity to restart classes. In destructive events, the commuting capacity can be affected by the structural damage of bridges, or by the inability to transit over blocked roads. In this context, the main objective of this research is to develop a methodology able to evaluate the risk of disruption to education caused by earthquakes and floods affecting both the physical school infrastructure in a region, and the road network that serves it. The proposed method integrates a Bayesian Network, a Monte Carlo simulation and an Agent-Based model to assess the interruption of the educational service. A substantial novelty of the proposed model is the integration of the community social vulnerability parameter with the physical vulnerability of the buildings, as both contributing to determine the operational capacity. This method is demonstrated via a case study of the province of San Pedro de Macoris in the Dominican Republic. Results show that the implementation of retrofitting strategies in school buildings and bridges can drastically reduce the education interruption time. Such improvement can be communicated with a simple, relatable cost metric—the cost of reducing one day of interruption per student—to provide meaningful insights for non-technical audiences and decision makers.