Rene J. LeClaire

Critical national infrastructure reliability modeling and analysis

One of the top 10 priorities of the U.S. Department of Homeland Security is protection of our critical national infrastructures including power, communications, transportation, and water. This paper presents models to quantify the interdependencies of critical infrastructures in the U.S. and evaluate plans to compensate for vulnerabilities. Communications is a key infrastructure, central to all others, so that understanding and modeling the risk due to communications disruptions is a high priority in order to enhance public safety and infrastructure resiliency. This paper discusses reliability modeling and analysis at a higher level than usual. Reliability analysis typically deals at the component or sub-system level and talks about “mean time to failure” and “mean time to repair” to derive availability estimates of equipment. Here, we deal with aggregate scales of failures, restoration, and mitigation across national infrastructures. This aggregate scale is useful when examining multiple infrastructures simultaneously with their interdependencies. System dynamics simulation models have been created for both communication networks and for the infrastructure interaction models that quantify these interactions using a risk-informed decision process for the evaluation of alternate protective measures and investment strategies in support of critical infrastructure protection. We will describe an example development of these coupled infrastructure consequence models and their application to the analysis of a power disruption and its cascading effect on the telecommunications infrastructure as well as the emergency services infrastructure. The results show significant impacts across infrastructures that can become increasingly exacerbated if the consumer population moves more and more to telecom services without power lifeline.

Telecom Critical Infrastructure Simulations: Discrete-Event Simulation vs. Dynamic Simulation How Do They Compare?

Critical national infrastructures for power, emergency services, finance, and other basic industries rely heavily on information and telecommunications networks (voice, data, and video) to provide services and conduct business. The telecommunication network is recognized by the federal government as one of the critical national infrastructures that must be maintained and protected against debilitating attacks. This paper describes a comparison between two simulation models of the voice telecommunications infrastructure for a metropolitan area for both wireline and wireless networks with millions of subscribers. One simulation is a very detailed discrete- event call-by-call simulation model, and the second is a higher level time-based system dynamics model. The purpose of these models is to investigate the availability of the telecom infrastructure under disruptions. The results show that the higher level system dynamics models can successfully match the summary results of the more detailed model and can be run several orders of magnitude faster.

An Integrated Simulation of Pandemic Influenza Evolution, Mitigation and Infrastructure Response

Decision makers, faced with highly complex alternatives for protecting our nations critical infrastructures must understand the consequences of policy options before they enact solutions to prevent and mitigate disasters. An effective way to examine these tradeoffs is to use a computer simulation that integrates high level representations of each infrastructure, their interdependencies and reactions to a variety of potential disruptions. To address this need, the Critical Infrastructure Protection Decision Support System (CIPDSS) project, funded by the Department of Homeland Security Science and Technology Directorate (DHS S&T), has developed a decision support tool that provides insights to help decision makers make risk-informed decisions. With the addition of a disease progression simulation, the CIPDSS tool has a unique ability to provide a high-level, integrated analysis of a pandemic influenza outbreak while representing the impact on critical infrastructures. This simulation models the time-dependent evolution of the disease and can be calibrated to prior data or to other higher fidelity models as appropriate. Mitigation options such as the use of antivirals and vaccines as prophylaxis, treatment or some combination as well as quarantine options can be assessed. Special attention is given to impacts to the population through sickness, targeted quarantine, or fear-based self-isolation and the resulting impacts on critical infrastructure operations.

Measuring the uncertainties of pandemic influenza

It has become critical to assess the potential range of consequences of a pandemic influenza outbreak given the uncertainty about its disease characteristics while investigating risks and mitigation strategies of vaccines, antivirals, and social distancing measures. Here, we use a simulation model and rigorous experimental design with sensitivity analysis that incorporates uncertainty in the pathogen behaviour and epidemic response to show the extreme variation in the consequences of a potential pandemic outbreak in the USA. Using sensitivity analysis we found the most important disease characteristics are the fraction of the transmission that occur prior to symptoms, the reproductive number, and the length of each disease stage. Using data from the historical pandemics and for potential viral evolution, we show that response planning may underestimate the pandemic consequences by a factor of two or more.