Joost Santos, The George Washington University
The objective of this presentation is to explore the development of hierarchical and multiregional decomposition models to better understand the dynamics of recovery in the aftermath of disasters. The vast majority of risk analysis studies on disasters and extreme events focus on preparedness and resilience measures for physical infrastructure systems. Nevertheless, significant research is severely lacking in areas of modeling, assessing, and managing the adverse impacts of disasters on the workforce. Although several studies underscore the enormous losses that can stem from workforce disruptions, there is currently no integrated modeling enterprise that is capable of modeling the impacts of disasters on coupled workforce infrastructure systems. A proof of concept will be demonstrated to address the following research questions: (i) how significant are the effects of disasters on workforce availability and how diverse are the resulting impacts on labor utilization across infrastructure and economic systems? (ii) what are the unique dynamic characteristics of post-disaster workforce availability that are different from the properties of infrastructure systems? (iii) how sensitive is the pace of regional recovery with respect to variations in levels of workforce availability and infrastructure functionality? and (iv) to what extent does prioritization of disaster management strategies across workforce and infrastructure systems alter the recovery timeline and regional losses? A dynamic input-output model formulation will also be introduced to define the resilience coefficient, or the capability of an economic sector to recover to its “business as usual” production status after a disruptive event. Case studies will be presented to describe the effects of various disasters on coupled workforce-infrastructure systems.