TIME-VARYING DISASTER RECOVERY MODEL FOR INTERDEPENDENT ECONOMIC SYSTEMS USING HYBRID INPUT--OUTPUT AND EVENT TREE ANALYSIS

Disasters damage physical infrastructure systems, disrupt the movement of people and commodities, and cause significant economic losses. This paper develops an I--O model extension using an event tree analysis to assess the propagation of disaster effects across interdependent economic sectors using the inoperability and economic loss metrics. Inoperability, a dimensionless index that ranges between 0 and 1, indicates the extent to which a sector's production deviates below its normal state. On the other hand, economic loss is the monetary worth of the drop in output incurred in each sector of the economy due to the disaster. The new dynamic I--O extension is capable of adjusting the inoperability parameters within the disaster timeline to reflect events that can either degrade or enhance the predicted paths of sector recovery. It was implemented to the Nashville region -- a metropolitan area in the USA known for its vibrant music and the tourism industry. The Nashville region is frequently hit by natural disasters such as tornadoes and floods, which makes it a suitable case study site for the model application. Results of the study can help identify critical economic sectors and ultimately provide insights for formulating preparedness decisions to expedite disaster recovery.