Effects of seismic risk analysis on regional sectors using both the deterministic and stochastic modeling

A natural disaster like an earthquake has the capability of damaging critical infrastructure systems, and valuable assets, limiting products or services movements, and in extreme conditions may cause injuries and even mortalities. The unavailability of a workforce as a response to an earthquake can directly affect the regional sector's productivity, as most business operations are labor dependent. In addition, the inherent interdependency of regional economic sectors can further delay the recovery process, This paper presents the dynamic inoperability input–output (DIIM) model and sector resilience to formulate a recovery analysis model by incorporating both the deterministic and stochastic modeling for workforce-interdependent sectors in the aftermath of an earthquake. The developed model is capable of evaluating the social and economic losses caused by workforce disruption. Moreover, a risk-based framework developed for the guidance of policymakers is to manage and control the adverse effects of the earthquake on the disrupted region. This paper identifies and prioritizes critical industry sectors based on two metrics i.e., inoperability and economic loss. Inoperability levels describe the percentage variation between the maximum production of the sector to the reduced production level, while economic loss is the quantified monetary value associated with the reduced level of sector output. The main contribution of this work focuses on the modeling of uncertainty caused by new disruption to the interconnected sectors within a recovery horizon of the initial outbreak of the disaster using a dynamic model for the disrupted region. This model is developed and applied to the regional sectors of Pakistan for an earthquake disaster but can be generalized to other regions and other disaster scenarios as well. Finally, the purpose of presenting different earthquake intensity scenarios is to validate the effective use of risk and uncertainty analysis in modeling the inoperability and economic loss behaviors because of time-varying perturbations and their related ripple effects on interdependent economic sectors.