Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis

Area of Science:

• Disaster management
• Economic modeling
• Public health

Background:

• Influenza pandemics pose significant threats to workforce availability and economic stability.
• Interdependencies between economic sectors amplify pandemic disruptions.
• Assessing pandemic impacts requires nuanced metrics beyond simple economic loss.

Purpose of the Study:

• To examine the impact of influenza pandemics on workforce availability across interdependent economic sectors.
• To analyze pandemic consequence propagation using a dynamic input-output simulation model.
• To evaluate critical economic sectors based on inoperability and economic loss metrics.

Main Methods:

• Utilized a dynamic input-output model for simulating pandemic impacts.
• Analyzed data from the 2009 H1N1 influenza pandemic.
• Employed inoperability and economic loss metrics to assess sector-specific impacts.

Main Results:

• Inoperability impacts were highest in hospital and health-care sectors.
• Economic loss impacts were most significant in sectors with high total production, like federal government agencies.
• Inoperability and economic loss metrics yielded distinct rankings of critical sectors.

Conclusions:

• Pandemic impact assessments should consider both inoperability and economic loss.
• Mitigation and recovery strategies need to balance these distinct metrics for effective policy.
• Understanding sector interdependencies is crucial for managing pandemic-induced economic disruptions.