Pandemic Influenza Impact on Workforce and Critical Infrastructure

NISAC models have been enhanced to simulate multiscale epidemiology and the public health infrastructure. NISAC analysts are using these models to examine disease spread at census-tract level nationally and at an individual level on a regional scale.

Using expected manifestations at the seasonal, 1958/68, and 1918 pandemic levels, explicit modeling of relevant aspects of the public health system has enabled NISAC to couple model output to population, workforce, infrastructure asset, and economic consequence assessments. Analyzed for geospatial structure, modeling output has revealed hotspots, strong correlations with average household size, and other demographic characteristics, emphasizing the importance of geospatial structure for pandemic planning at the local level.

Selected aspects of proposed national pandemic plans, mitigation, and response options are being simulated in this ongoing project. In-depth sensitivity analysis is planned for strategies deemed most effective and robust.

Pandemic Influenza Policy Analysis

Conclusions from the epidemiological and mitigation strategy analyses conducted to date include:

• Response time is most important, other factors are secondary.
• Partially effective response early is best.
• Geospatial dynamics are important.
• Face masks can reduce or prevent an epidemic.
• Border control can only delay an epidemic, and a 95% reduction in the contagious individuals entering the country delays the epidemic by 5 weeks.
• Social distancing is also effective in delaying an epidemic, but returning to normal interactions without other mitigation measures causes waves of outbreaks. This strategy corresponds to historical interventions and disease outbreaks.

Working in collaboration with the DHS Science and Technology’s Critical Infrastructure Protection Decision Support System (CIPDSS) program, NISAC developed models of workforce impacts on infrastructure operations. We will use these models to evaluate pandemic effects on infrastructures and provide input to the analysis of national economic impacts.

Modeling/Analysis Approach

NISAC

• Translated epidemiological results, using population and workforce data, into impacts on labor categories by infrastructure, industry, and commercial sector.
• Modeled functional relationships of labor categories on infrastructure operations for each sector.
• Used reductions in workforce to estimate reductions in infrastructure service provision.
• Modeled impacts of mitigation strategies on workforce and used the results to estimate impacts on infrastructure service provision.

NISAC uses systems models of infrastructures to evaluate the effects of labor shortages on operations (transportation, telecom, and energy) and data analysis to develop labor models for the other infrastructures (banking and finance, water, government, agriculture/food, etc.). Different processes in infrastructure supply chains are represented in the model and include the effects on the workforce due to illness, parents having to stay home with sick children, employees refusing to go to work out of fear (worried well), and fatigue in staff that are working extraordinary hours.

The NISAC and CIPDSS approach to estimating the economic impacts of a pandemic are comprehensive and multi- dimensional, based on known interactions between labor supply, industry output, consumer demand, and households. By having the economics modeling take a systems approach that is similar to the epidemiological and infrastructure modeling approach, a rich environment is created for cross-model comparison and validation.

Estimating the Economic Impacts of a Pandemic Influenza

NISAC applied a central model of how firms adapt to labor losses, under varying epidemiological and government response conditions, to estimate the impacts of pandemic morbidity and mortality on infrastructures, their interdependencies, and the economy. Analyses include identifying infrastructure and economic vulnerabilities caused by labor losses and overall economic conditions. Estimates are made of

• firm-level responses by industry, firm-size, and policy taken;
• socio-demographic effects; and
• regional and national short-run and long-run losses in output, employment, trade, and price levels.

Scenario

NISAC simulated a magnitude 9.0 earthquake along the Cascadia fault, with a tsunami resulting from the earthquake. We then used the ground shaking and tsunami effects to assess the scenario’s infrastructure impacts. The analysis assumes that the disaster event takes place at the current time and proceeds by evaluating human impacts and cascading infrastructure effects within the earthquake impact zone. Finally, we estimated economic impacts. Each of these impact areas (human, infrastructure, and economic) are summarized in the key findings below.

Key Findings

Human Impacts

This study first examined the impacts of the earthquake and tsunami on the human population within the affected area. The expected damage and loss of life would occur along the coastal regions of northern California, Oregon, and Washington. The analysis produced an estimate of 3,000 or more fatalities from the tsunami and ground-shaking effects.

Major Infrastructure Impacts

The entire region would experience extensive electrical outages, with medium-term outages forecast for the coastal areas. Restoration is expected to occur on a prioritized basis within one to eight days. Both the natural gas transmission pipeline and the networks of distribution pipelines in the affected region are likely to suffer enough damage for the majority of customers in western Washington and western Oregon to lose natural gas service. Major undersea transoceanic cables are likely to be severed, disrupting communication service to East Asia as well as between Alaska and the contiguous United States, with a two- to three-month expected restoration time.

Economic Impacts

The total economic impacts are projected to be nearly $70 billion, with nearly $20 billion of that in direct impacts and nearly $50 billion in indirect impacts. Washington State has the largest share (70 percent), with $11 billion in direct and $38 billion in indirect impacts.