A stochastic recovery model of influenza pandemic effects on interdependent workforce systems

Outbreaks of infectious diseases, such as pandemics, can result in adverse consequences and major economic losses across various economic sectors. Based on findings from the 2009 A H1N1 pandemic in the National Capital Region (NCR), this paper presents a recovery analysis for workforce disruptions using economic input–output modeling. The model formulation takes into consideration the dynamic interdependencies across sectors in an economic system in addition to the inherent characteristics of the economic sectors. From a macroeconomic perspective, the risk of the influenza disaster can be modeled using two risk metrics. First, there is the level of inoperability, which represents the percentage difference between the ideal production level and the degraded production level. Second, the economic loss metric represents the financial value associated with the reduced output. The contribution of this work revolves around the modeling of uncertainties triggered by new perturbations to interdependent economic sectors within an influenza pandemic timeline. We model the level of inoperability of economic sectors throughout their recovery horizon from the initial outbreak of the disaster using a dynamic model. Moreover, we use the level of inoperability values to quantify the cumulative economic losses incurred by the sectors within the recovery horizon. Finally, we revisit the 2009 NCR pandemic scenario to demonstrate the use of uncertainty analysis in modeling the inoperability and economic loss behaviors due to time-varying perturbations and their associated ripple effects to interdependent economic sectors.